3D Printed Helix Antenna for 77 GHz - Lomakin, Konstantin; Sippel, Mark; Ullmann, Ingrid; Helmreich, Klaus; Gold, Gerald (2020 14th European Conference on Antennas and Propagation (EuCAP), 2020)
In this work, an additively manufactured helix antenna for a center frequency of f c = 77 GHz is presented. A novel feed concept is proposed including a transition from the helix coil to an E-band waveguide, which allows for tuning of antenna matching. Measurements suggest a -15dB-bandwidth of B 15 dB =8 GHz and -10dB-bandwidth of B 10 dB =16 GHz respectively with a fractional -10dB-bandwidth of 20 %. An axial ratio below AR<; 5 dB is achieved within the entire B-10 dB and even AR<; 3 dB within B-15 dB in main lobe direction. The realized antenna gain ranges at G LP ≈11 dBi in linear polarization component yielding a circular polarization gain of G CP ≈12 to 13 dBi. Hence, measurements suggest general feasibility of the proposed helix antenna for mmWave applications despite the relatively high structure complexity due to the miniaturized dimensions at the aimed frequencie

3D Printed Hemispherically Radiating Antenna for Broadband Millimeter Wave Applications - Engel, Lukas; Khouri, Danti; Lomakin, Konstantin; Hofmann, Andreas; Kleinlein, Micha; Ullmann, Ingrid; Vossiek, Martin; Gold, Gerald (IEEE Open Journal of Antennas and Propagation, 2023)
Nowadays, additive manufacturing provides far-reaching possibilities for use in radio frequency components. In addition to almost unlimited freedom of design as compared to conventional manufacturing, the absence of further assembly steps is a key aspect of 3D printing. In this paper, a 3D printed monolithic antenna for millimeter wave-sensing applications is presented with a full hemispherical coverage. The antenna is designed as an ensemble of a waveguide horn antenna and a differentially fed dipole antenna. The slotted waveguide approach was utilized to improve the manufacturing quality on the waveguide inside. The influence of two optimized antenna elements, a metal plane, and a cut-out window, on the beam pattern is comprehensively investigated. A huge half power beam width of 142° in both directions, elevation and azimuth, is presented at 79 GHz and a boresight gain of 4.7 dBi was measured. The beam pattern in the frequency range from 76 to 81 GHz is studied in greater detail, where a half power beam width of at least 112° is achieved. Due to the −10 dB matching capability bandwidth of over 28 GHz, the antenna is also suitable for extremely broadband applications with a −5 dB angular width of better than 100°. Furthermore, the system design describes how to integrate the antenna into hybrid circuit designs and the manufacturing tolerances are examined. The antenna offers attractive possibilities for millimeter wave-sensing applications in the area of assisted living and industrial monitoring, especially whenever blind spots have to be avoided.<br

A Computationally Efficient Reconstruction Approach for Imaging Layered Dielectrics With Sparse MIMO Arrays - Ullmann, Ingrid; Vossiek, Martin (IEEE Journal of Microwaves, 2021)
This contribution presents a novel, computationally efficient approach to radar imaging of layered dielectrics with sparse MIMO arrays. Our concept does not impose any constraints on the array topology and at the same time promises to be more efficient than the state-of-the-art backprojection algorithm because it can make use of k-space reconstruction schemes. Experimental results with a sparse, non-equidistantly sampled array are provided. These demonstrate the feasibility of the approach and that the computational burden could be reduced by several orders of magnitude in a given practical example related to radar based non-destructive testin

Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data - Engel, Lukas; Müller, Jonas; Rendon, Eduardo Javier Feria; Dorschky, Eva; Krauß, Daniel; Ullmann, Ingrid; Eskofier, Björn; Vossiek, Martin (IEEE Journal of Microwaves, 2025)
This paper presents a deep learning-enabled method for human pose estimation using radar target lists, obtained through a low-cost radar system with three transmitters and four receivers in a multiple-input multiple-output setup. We address challenges in previous research that often relied on extracting ground truth poses from RGB data, which are constrained by the need for 3D mapping and vulnerability to occlusions. To overcome these limitations, we utilized optical motion capture, which is widely recognized as the gold standard for precise human motion analysis. We conducted an extensive optical motion capture study involving various recorded movement activities, which resulted in mmRadPose, a new dataset that enhances existing benchmarks for radar-based pose estimation. This dataset has been made publicly accessible. Building on this approach, we designed an application-tailored radar signal processing chain to generate suitable input for the machine learning algorithm. We further developed an attentional recurrent-based deep learning model, PntPoseAT, which predicts 24 keypoints of human poses using radar target lists. We employed cross validation to thoroughly evaluate the model. This model surpasses previous approaches and achieves an average mean per-joint position error of 6.49 cm with a standard deviation of 3.74 cm on totally unseen test data. This excellent accuracy of the reconstructed keypoint positions is particularly remarkable when you consider that a very simple radar was used for the measurements. Additionally, we conducted a comprehensive analysis of the model's performance by exploring aspects such as network architecture, the use of long short-term memory versus gated recurrent units, input data selection, and the integration of multi-head self-attention mechanism
Keywords: Human pose estimation; radar; optical motion capture; millimeter wave; target list; point cloud; machine learning; deep learning; Radar; Pose estimation; Deep learning; Skeleton; Laser radar; Sensors; Radar measurements; Motion capture; Cameras; Synchronization

A Feasibility Study on the Use of Microwave Imaging for In-Vivo Screening of Knee Prostheses - Root, Konstantin; Ullmann, Ingrid; Seehaus, Frank; Vossiek, Martin (International Microwave Symposium, 2020)
This article provides a concept study on the feasibility of microwave imaging for in vivo screening of knee implants. Using microwave imaging for condition monitoring avoids patients’ exposure to X-ray, which is hazardous to human health. Therefore, investigating the potentials of such a technique is worthwhile. Two essential aspects were investigated in the study: 1) the propagation properties of human tissue and 2) the imaging capabilities of microwave synthetic aperture radar (SAR) for screening polyethylene knee inlays. The first point addresses the challenge of strong absorption in tissue, which contains a high percentage of water. Quantitative investigations were performed. For imaging, SAR with a cylindrical synthetic aperture was constructed to account for the convex geometry of the human knee. An imaging concept that considers material properties and refraction was developed to yield a highly focused image. From the results of the two issues, an imaging concept was deduced that could enable a microwave-based screening of the human knee in the future.

A Millimeter-Wave MIMO Radar Network for Human Activity Recognition and Fall Detection - Fröhlich, Ann-Christine; Mejdani, Desar; Engel, Lukas; Bräunig, Johanna; Kammel, Christoph; Vossiek, Martin; Ullmann, Ingrid (2024 IEEE Radar Conference (RadarConf24), 2024)

A MIMO ISAR Approach with Depth Camera Motion Tracking for Improved Imaging in Walk-Through Security Scanners - Root, Konstantin; Gumbmann, Frank; Adametz, Julian; Ullmann, Ingrid; Vossiek, Martin (2023 IEEE International Radar Conference (RADAR), 2023)

A Multimodal Radar-Ultrasound Imaging Concept for Improved Display of Concealed Objects - Ullmann, Ingrid; Körner, Georg; Adametz, Julian; Vossiek, Martin (IEEE Access, 2019)
Subsurface radar imaging provides an insight into hidden scenes: For example, in security screening, radar can be used for the detection of dangerous objects or contraband. In non-destructive testing, radar imaging also allows to find internal material defects such as cracks or contaminations. Object contours and internal structures appear as echoes in the radar receive signal. The strongest echo typically is the one from the test object’s surface. This echo can mask smaller echoes close to the surface and therefore, small inner structures may become invisible in the reconstruction image. To overcome this problem, we propose a novel concept to eliminate the surface echo in radar imaging. In contrast to existing surface elimination techniques, our approach can be used not only when screening objects with planar surfaces, but also on such that exhibit an unknown and possibly non-planar profile. Our approach is to combine radar and air-coupled ultrasound. Since air-coupled ultrasound cannot penetrate into solids, the receive signal only contains the echo from the test object’s surface. The core of our concept is to generate radar and ultrasound signals with the same characteristics, i.e. they are equal in amplitude and phase. Then, the ultrasound data can be subtracted from the radar data and the resulting signal will only contain the echoes of the inner structures. When processing this data, the reconstructed images are almost free of reflections from the surfac

An Efficient yet High-Performance Method for Precise Radar-Based Imaging of Human Hand Poses - Bräunig, Johanna; Wirth, Vanessa; Stamminger, Marc; Ullmann, Ingrid; Vossiek, Martin (2024 21st European Radar Conference, EuRAD 2024, 2024)
Contactless hand pose estimation requires sensors that provide precise spatial information and low computational complexity for real-Time processing. Unlike vision-based systems, radar offers lighting independence and direct motion assessments. Yet, there is limited research balancing real-Time constraints, suitable frame rates for motion evaluations, and the need for precise 3D data. To address this, we extend the ultra-efficient two-Tone hand imaging method from our prior work to a three-Tone approach. Maintaining high frame rates and real-Time constraints, this approach significantly enhances reconstruction accuracy and precision. We assess these measures by evaluating reconstruction results for different hand poses obtained by an imaging radar. Accuracy is assessed against ground truth from a spatially calibrated photogrammetry setup, while precision is measured using 3D-printed hand poses. The results emphasize the method's great potential for future radar-based hand sensing.
CRIS-Team Scopus Importer:2024-12-13
Keywords: FSK radar; gesture recognition; hand pose estimation; radar imaging; three-frequency principle

A Novel Antenna Placement Algorithm for Compressive Sensing MIMO Radar - Eisele, Bastian; Bereyhi, Ali; Ullmann, Ingrid; Müller, Ralf (2023 IEEE Radar Conference (RadarConf23), 2023)
In colocated compressive sensing MIMO radar, the measurement matrix is specified by antenna placement. To guarantee an acceptable recovery performance, this measurement matrix should satisfy certain properties, e.g., a small coherence. Prior work in the literature often employs randomized placement algorithms which optimize the prior distribution of antenna locations. The performance of these algorithms is suboptimal, as they can be easily enhanced via expurgation. In this paper, we suggest an iterative antenna placement algorithm which determines the antenna locations deterministically. The proposed algorithm locates jointly the antenna elements on the transmit and receive arrays, such that the coherence of the resulting measurement matrix is minimized. Numerical simulations demonstrate that the proposed algorithm outperforms significantly the benchmark, even after expurgatio
Keywords: Compressive sensing; MIMO radar; Antenna placement; coherence

A Novel, Efficient Algorithm for Subsurface Radar Imaging below a Non-Planar Surface - Ullmann, Ingrid; Vossiek, Martin (Sensors, 2023)
In classical radar imaging, such as in Earth remote sensing, electromagnetic waves are usually assumed to propagate in free space. However, in numerous applications, such as ground penetrating radar or non-destructive testing, this assumption no longer holds. When there is a multi-material background, the subsurface image reconstruction becomes considerably more complex. Imaging can be performed in the spatial domain or, equivalently, in the wavenumber domain (k-space). In subsurface imaging, to date, objects with a non-planar surface are commonly reconstructed in the spatial domain, by the Backprojection algorithm combined with ray tracing, which is computationally demanding. On the other hand, objects with a planar surface can be reconstructed more efficiently in k-space. However, many non-planar surfaces are partly planar. Therefore, in this paper, a novel concept is introduced that makes use of the efficient k-space-based reconstruction algorithms for partly planar scenarios, too. The proposed algorithm forms an image from superposing sub-images where as many image parts as possible are reconstructed in the wavenumber domain, and only as many as necessary are reconstructed in the spatial domain. For this, a segmentation scheme is developed to determine which parts of the image volume can be reconstructed in the wavenumber domain. The novel concept is verified by measurements, both from monostatic synthetic aperture radar data and multiple-input–multiple-output radar data. It is shown that the computational efficiency for imaging irregularly shaped geometries can be significantly augmented when applying the proposed concep
Keywords: radar; subsurface imaging; synthetic aperture radar; ground penetrating radar; MIMO radar; non-destructive testing

An Ultra-Efficient Approach for High-Resolution MIMO Radar Imaging of Human Hand Poses - Bräunig, Johanna; Wirth, Vanessa; Kammel, Christoph; Schüßler, Christian; Ullmann, Ingrid; Stamminger, Marc; Vossiek, Martin (IEEE Transactions on Radar Systems, 2023)
The capturing of hands, including their poses, shapes and motions, has numerous potential applications, such as human-machine interfaces and medical use cases. However, in the radar context, most existing methods only allow for the recognition of dynamic hand gestures based on Doppler evaluations due to the respective systems’ limited lateral resolution. Radar-based high-resolution three-dimensional (3D) imaging using multiple-input multiple-output (MIMO) radars is currently the state-of-the-art in personnel security scanning. However, the associated imaging techniques suffer from computationally burdensome reconstruction algorithms that sample the entire 3D space of interest, thereby making them less suitable for real-time applications. Moreover, their application in hand motion tracking scenarios is limited by low frame rates that result from a high number of transmit frequencies. Hence, we present an efficient and powerful approach for the radar-based 3D reconstruction of hand poses. The method extends the frequency shift keying continuous wave radar principle and reconstructs the hand surface using only two carrier frequencies. Instead of reconstructing an entire 3D volume, only two single-tone radar images are computed. Depth information is derived from phase differences between corresponding pixels in the images. The approach significantly reduces computational load by three orders of magnitude compared with the state-of-the-art and enables higher frame rates. Within this paper, this novel reconstruction principle is analyzed and compared to a state-of-the-art radar imaging approach using a MIMO radar system with 94 transmitting and 94 receiving antennas. Detailed simulations of point targets and comprehensive measurements demonstrate the excellent imaging performance of our approac

A Radar-Based Concept for Simultaneous High-Resolution Imaging and Pixel-Wise Velocity Analysis for Tracking Human Motion - Bräunig, Johanna; Heinrich, Simon; Coppers, Birte; Kammel, Christoph; Wirth, Vanessa; Stamminger, Marc; Leyendecker, Sigrid; Liphardt, Anna-Maria; Ullmann, Ingrid; Vossiek, Martin (IEEE Journal of Microwaves, 2024)
The radar-based analysis of human motion is actively being researched due to its contact- and markerless nature and ability to measure motion directly via the Doppler effect. Especially in medical and biomechanical fields, precise movement analysis is crucial. However, existing radar-based studies typically exhibit low lateral resolution, focusing on velocity evaluations and the tracking of scattering centers resolvable in the range or Doppler domains. In this work, we present a novel concept that enables a pixel-wise velocity analysis of human motion in radar near-field imaging scenarios. For this, we utilize the well-established back-projection technique to reconstruct consecutive radar images and perform a subsequent pixel-wise phase comparison. To accurately capture pixel-specific velocities along the depth dimension, this is followed by corrections of near-field geometry distortions accounting for aperture properties and pixel positions. Our theoretical derivations are supported by comprehensive point target simulations. To assess the performance of the proposed approach, we conducted a proof-of-concept study. We tracked a hand surface's movement while performing a finger tapping motion and compared the fingertip position and velocity determined by the radar with the respective values obtained from an optical marker-based system. The results showed a velocity measurement accuracy of 8.1mms−1 and a tracking accuracy of 1.4mm , demonstrating the great potential of our approach. The high angular resolution of the velocity measurement enables the tracking of the entire illuminated body shell, extending the range of future applications of radar-based motion analysis.<br
Keywords: Radar tracking; Radar; Radar imaging; Radar antennas; MIMO radar; Velocity measurement; Target tracking; Doppler radar; Signal resolution; Scattering; Human motion tracking; near-field imaging; radar imaging; velocity measurement

A Realistic Radar Ray Tracing Simulator for Hand Pose Imaging - Bräunig, Johanna; Schüßler, Christian; Wirth, Vanessa; Stamminger, Marc; Ullmann, Ingrid; Vossiek, Martin (EuRAD 2023, 2023)
With the increasing popularity of human-computer interaction applications, there is also growing interest in generating sufficiently large and diverse data sets for automatic radar-based recognition of hand poses and gestures. Radar simulations are a vital approach to generating training data (e.g., for machine learning). Therefore, this work applies a ray tracing method to radar imaging of the hand. The performance of the proposed simulation approach is verified by a comparison of simulation and measurement data based on an imaging radar with a high lateral resolution. In addition, the surface material model incorporated into the ray tracer is highlighted in more detail and parameterized for radar hand imaging. Measurements and simulations show a very high similarity between synthetic and real radar image captures. The presented results demonstrate that it is possible to generate very realistic simulations of radar measurement data even for complex radar hand pose imaging systems. <br
Keywords: radar simulation; ray tracing; radar imaging; human-computer interaction; hand pose recognition.

A Realistic Radar Ray Tracing Simulator for Large MIMO-Arrays in Automotive Environments - Schüßler, Christian; Hoffmann, Marcel; Bräunig, Johanna; Ullmann, Ingrid; Ebelt, Randolf; Vossiek, Martin (IEEE Journal of Microwaves, 2021)
With the rise of high resolution multiple input multiple output (MIMO) systems, radar became an important sensor in the development of Advanced Driver Assistance Systems (ADAS) and autonomous driving applications. Autonomous driving will rely strongly on artificial intelligence. Since most modern classification algorithms are based on neural networks, they require huge amounts of data to perform well, especially in unexpected traffic situations. Radar sensor simulation can potentially produce a great variety of training data for machine learning algorithms, which makes it an important cornerstone in the development of ADAS. Furthermore, with radar simulators, different antenna configurations and various edge cases can be simulated. In this work, a versatile ray tracing toolchain based on the shoot and bouncing rays (SBR) approach is presented. The program is able to simulate complex urban environments including realistic clutter, by utilizing simplistic reflection models. The program does not only produce realistic radar images, but also generates camera-like images using the same materials. Furthermore, this work deals with the adaption of the SBR method to radar sensors with an arbitrary number of transmit (TX)- and receive (RX) antennas, which enables the simulation of large MIMO arrays. A novel performance optimization approach is proposed for large numbers of TX antennas, which reduces the runtime dramatically. The quality of the simulation is verified by measuring a complex and realistic scenario with a high resolution automotive MIMO radar. Also, a study of the effect on quality and runtime is being investigated for various optimization approaches, including the proposed method.
Keywords: Radar; Radar antennas; Solid modeling; Computational modeling; Antennas; Scattering; Radar cross-sections; MIMO radar; radar simulation; ray tracing; shoot and bouncing rays

A Review and Tutorial on Machine Learning- Enabled Radar-Based Biomedical Monitoring - Krauß, Daniel; Engel, Lukas; Ott, Tabea; Bräunig, Johanna; Richer, Robert; Gambietz, Markus; Albrecht, Nils; Hille, Eva M; Ullmann, Ingrid; Braun, Matthias; Dabrock, Peter; Kölpin, Alexander; et al. (IEEE Open Journal of Engineering in Medicine and Biology, 2024)
Radio detection and ranging-based (radar) sensing offers unique opportunities for biomedical monitoring and can help overcome the limitations of currently established solutions. Due to its contactless and unobtrusive measurement principle, it can facilitate the longitudinal recording of human physiology and can help to bridge the gap from laboratory to real-world assessments. However, radar sensors typically yield complex and multidimensional data that are hard to interpret without domain expertise. Machine learning (ML) algorithms can be trained to extract meaningful information from radar data for medical experts, enhancing not only diagnostic capabilities but also contributing to advancements in disease prevention and treatment. However, until now, the two aspects of radar-based data acquisition and ML-based data processing have mostly been addressed individually and not as part of a holistic and end-to-end data analysis pipeline. For this reason, we present a tutorial on radar-based ML applications for biomedical monitoring that equally emphasizes both dimensions. We highlight the fundamentals of radar and ML theory, data acquisition and representation and outline categories of clinical relevance. Since the contactless and unobtrusive nature of radar-based sensing also raises novel ethical concerns regarding biomedical monitoring, we additionally present a discussion that carefully addresses the ethical aspects of this novel technology, particularly regarding data privacy, ownership, and potential biases in ML algorithms.
Keywords: Radar; Biomedical monitoring; Doppler effect; Doppler radar; Sensors; Radar measurements; Radar applications; Radar; Machine Learning; Medicine; Ethics; Biomedical Monitoring

A Review on Ultrasound-based Methods to Image the Distribution of Magnetic Nanoparticles in Biomedical Applications - Huber, Christian; Pavan, Theo Z.; Ullmann, Ingrid; Heim, Christian; Rupitsch, Stefan J.; Vossiek, Martin; Alexiou, Christoph; Ermert, Helmut; Lyer, Stefan (Ultrasound in Medicine and Biology, 2024)
Magnetic nanoparticles (MNPs) have gained significant attention in biomedical engineering and imaging applications due to their unique magnetic and mechanical properties. With their high magnetization and small size, MNPs serve as excitation sources for magnetically heating to destroy tumors (magnetic hyperthermia) and magnetically controlled drug carriers in magnetic drug targeting. However, effectively visualizing the distribution of MNPs during research or potential clinical use with low-cost modalities remains a critical challenge. Although magnetic resonance imaging provides pre- and post-procedural imaging, it is considered to be high cost, and real-time imaging during clinical procedures is limited. In contrast, ultrasound-based imaging methods offer the advantage of providing the potential for immediate feedback during clinical use and are considered to be a low-cost modality. Ultrasound-based imaging techniques, including magnetomotive ultrasound, magnetoacoustic tomography, and thermoacoustic imaging, emerged as promising approaches for imaging the distribution of MNPs. These techniques offer the potential for real-time imaging, facilitating precise therapy monitoring. By exploring the strengths and limitations of various ultrasound-based imaging techniques for MNPs, this review seeks to provide comprehensive insights that can guide researchers in selecting suitable ultrasound-based modalities and inspire further advancements in this exciting field.
CRIS-Team Scopus Importer:2024-11-22
Keywords: Magnetic nanoparticles; Magnetoacoustic tomography; Magnetomotive ultrasound; Thermoacoustic imaging; Tomography; Ultrasound-based imaging

A Survey on Radar-Based Continuous Human Activity Recognition - Ullmann, Ingrid; Guendel, Ronny; Kruse, Nicolas Christian; Fioranelli, Francesco; Yarovoy, Alexander (IEEE Journal of Microwaves, 2023)
Radar-based human motion and activity recognition is currently a topic of great research interest, as the aging population increases and older individuals prefer an independent lifestyle. This technology has a wide range of applications, such as fall detection in assisted living, gesture recognition for human-machine interfaces, and many more. Numerous studies exist on various approaches for radar-based activity capture and classification. However, most of these employ rather artificial data, often obtained in laboratory environments, and typically collected under particular conditions. Specifically, most research so far has aimed at distinguishing a predefined set of single activities with a defined start, stop and duration. This paper aims at drawing the attention to a so far less researched issue, one that will be of vital importance for future real-world application of radar-based human activity recognition: continuous activity recognition, i.e. recognizing specific activities in a stream of several sequential activities with unknown duration and arbitrary transitions between different classes of activities. A review on the current state of the art in this relatively new topic is given, followed by a discussion on future research directions.<br

Automated Defect Detection for Non-Destructive Evaluation by Radar Imaging and Machine Learning - Ullmann, Ingrid; Egerer, Pascal; Schür, Jan; Vossiek, Martin (13th German Microwave Conference (GeMiC 2020), 2020)
This work provides a concept for a fully automated, non-invasive evaluation of dielectric objects by use of synthetic aperture radar (SAR) imaging combined with machine learning for application in non-destructive evaluation (NDE). For demonstration purposes we investigated a set of polyvinylchloride (PVC) test objects. A millimetre-wave imaging system is used to scan the objects. By employing subsurface SAR imaging techniques, high-resolution images from the objects’ insides can be obtained. These images are used as a dataset for a convolutional neural network. By training the network on several typical defect structures such as cracks, delaminations or contaminations, the proposed procedure enables an automated decision whether an object under test is intact or defective, independent of the kind of defec

Chipless RFID Polarimetric Radar Barcodes Encoded by Dipole Scattering Domains - Stief, Patrick; Ullmann, Ingrid; Körner, Georg; Root, Konstantin; Vossiek, Martin (IEEE Journal of Microwaves, 2022)
Recently, a novel chipless radio-frequency identification (RFID) concept based on polarimetric radar barcodes was introduced. These tags are similar to the well known optical quick response codes (QR codes). In polarimetric radar barcodes the information is stored as polarimetrically coded areas arranged in a grid and read out by an imaging radar. This paper presents a novel concept for elegantly creating polarimetric barcodes based on dipole scattering domains. Each scattering domain consists of several hundred dipoles. The dipoles are either uniformly arranged at a specific angle, which produces a specific angle-dependent polarization response, or randomly oriented to produce an unpolarized response. In order to read out the polarimetric information stored in the tags, the position and rotation of the radar barcodes needs to be determined. Our research reveals that using three reference elements and a novel decoding algorithm, a position- and rotation-tolerant readout is possible. To reduce distortions caused by the surface of the structure carrying the dipoles, different matching layer concepts were investigated. The novel chipless RFID tag concept is tested using a fully polarimetric W-band (75-110GHz) imaging radar. The implemented setup allows for a theoretical data capacity of 1.92bit/cm2 on a single layer PCB. In our measurements, we achieved a data capacity of 1.52bit/cm2. Utilizing the chosen tag size of 45mm×45mm resulted in a tag with a greater than 30 bit data capacity, which is an excellent value for chipless RFID.<br
Keywords: Chipless radio-frequency identification (RFID); image processing; millimeter wave; radar imaging; RFID

Circular Polarization Millimeter-Wave SAR Imaging using 3D-Printed Helix Antennas - Ullmann, Ingrid; Root, Konstantin; Lomakin, Konstantin; Gold, Gerald; Gottinger, Michael; Helmreich, Klaus; Vossiek, Martin (SPIE Security + Defense Forum, 2020)
We propose the use of 3D-printed helix antennas for millimeter-wave radar imaging. This concept is promising for a number of reasons: Additive manufacturing involving 3D-printing is a relatively cost efficient fabrication technique and offers increased geometrical freedom of design compared to conventional manufacturing processes. From an imaging point of view, using helix antennas is advantageous because of the circular polarization the antennas emit. That way, imaging thin dipole-like structures is possible regardless of their orientation. In contrast, imaging systems using linearly polarized antennas are unable to image dipoles orientated orthogonally to their polarization direction. Radar systems using circular polarization additionally enable polarimetric imaging and decomposition. In security screening this can achieve a higher classification accuracy in discriminating threat objects and reduce false alarms. Furthermore, the thin helix antennas (typical coil diameter: ca. 1.5 mm) can be mounted very closely to each other, which is interesting for array design. A security screening example was investigated for demonstration: A cardboard box with metallic and dielectric threat objects was screened at 70 GHz – 90 GHz by a quasi-monostatic synthetic aperture radar consisting of two 3D-printed helix antennas, one right-hand and one left-hand circularly polarized. As a reference, the same object was screened with split-block linearly polarized horn antennas. With the proposed setup, the resolution of the reconstruction images was comparable to that of the reference system. However, the circular polarization was able to depict thin structures in a better fashion than the linearly polarized reference system.

Classification Strategies for Radar-Based Continuous Human Activity Recognition with Multiple Inputs and Multi-Label Output - Ullmann, Ingrid; Guendel, Ronny G.; Kruse, Nicolas Christian; Fioranelli, Francesco; Yarovoy, Alexander (IEEE Sensors Journal, 2024)
Fall detection systems can play an important role in assuring safe independent living for vulnerable people. These sensors not only have to detect falls, but also have to recognize uncritical, normal activities of daily living in order to differentiate them from falls. Radar sensors are very attractive for human activity recognition thanks to their contactless capabilities and lack of plain videos recorded. In this paper, a novel approach to recognize single activities in a continuous stream of radar data is proposed, whereby the stream is divided into windows of fixed length and then multi-label classification is used to recognize all activities taking place in these time segments. While the initial feasibility of this approach was presented in an earlier contribution presented at the 2023 IEEE SENSORS conference, in this extended work additional in-depth studies on critical parameters are performed. Specifically, multiple combinations of different radar data domains/representations (e.g., range-time maps, range-Doppler maps and spectrograms) and different radar nodes in a network of five cooperating sensors are considered as inputs to two considered multi-label classification networks. Additionally, a parametric study on the probability thresholds of the networks to assign labels to specific classes is also performed.
CRIS-Team Scopus Importer:2024-08-02
Keywords: Activities of daily living; deep learning; Doppler effect; Fall detection; Human activity recognition; human activity recognition; Legged locomotion; multi-label classification; radar; Radar; Sensors; Spectrogram

Close range ISAR imaging with target velocity determination for security screening applications - Root, Konstantin; Ullmann, Ingrid; Gmehling, Stefan; Vossiek, Martin (Emerging Imaging and Sensing Technologies for Security and Defence VI SPIE Security + Defence, 2021)
State-of-the-art personnel screening systems reconstruct images by using multiple-input-multiple-output (MIMO) radars, which require a large number of transmit and receive channels along a two-dimensional array. We propose a novel concept for security screening which does not require the person to stand still and only employs a one- dimensional array: Our approach is built on the use of inverse synthetic aperture radar (ISAR) imaging based on a vertical line array. This means that the moving person inversely samples a synthetic aperture along the horizontal dimension. In order to reconstruct an image by the ISAR principle, the test subject's velocity relative to the radar aperture needs to be known. Therefore, we employ an additional radar module which measures the person's velocity, assuming that the person is moving parallel to the aperture plane. Experiments with a mannequin carrying threat objects were performed. The mannequin was moved on a traversing rail with 1 m/s and its velocity was estimated by a commercial radar module emitting a chirp sequence signal. The estimation was in very good accordance with the rail's real moving speed. With the determined target velocity an image was reconstructed along the horizontal direction by the ISAR principle. Along the vertical direction, the focusing was performed using a MIMO line array of 45 transmitter and 24 receiver channels with a total height of 60 cm. That way, and by employing broadband signals (70 GHz - 80 GHz), three-dimensional high-resolution images were obtainable. Promising results were obtained from the measurements and different threat objects were made visible.
Keywords: Radar; Velocity measurements; Image resolution; Synthetic aperture radar; Imaging arrays; Radar imaging; Scanners

Combining radar and ultrasound imaging for surface echo compensation and augmented visibility of interior structures in NDT applications - Ullmann, Ingrid; Schür, Jan; Vossiek, Martin (13th European Conference on Non-Destructive Testing (ECNDT), 2023)
Millimeter-wave radar imaging is a promising technique in non-destructive testing. When a small material defect is located closely to the test object’s surface, the strong reflection caused by the air-material interface can overlap with the defect’s weak reflection and mask it. If the image resolution is not sufficient, the defect cannot be resolved and will not be recognizable in the reconstruction image. To solve this problem, surface echo compensation techniques have been invented. However, these techniques are usually restricted to planar surfaces, which for most applications is not the case. This article presents a technique for surface echo compensation of arbitrarily shaped objects. We propose to combine radar and air-coupled ultrasound. Since air-coupled ultrasound is not able to penetrate solids, an air-coupled ultrasound imaging system is only able to detect the surface of a solid object. The idea of our proposed concept is to employ the ultrasound signal to compensate for the surface echo in the radar signal. The proposed method is based on the idea of using signals of equal wavelengths for both wave types and an amplitude calibration. Then, the resulting signals for radar and ultrasound are formally equal, which makes it possible to directly combine them numerically. That way, a modified radar image can be obtained which only contains the reflections from the inside and highlights interior defect

Contactless Inspection of Handwritten Documents with Terahertz Imaging - Ullmann, Ingrid; Root, Konstantin; Schür, Jan; Scheuble, Lorenz; Vossiek, Martin (18th European Radar Conference (EuRAD 2021), 2022)
This paper presents results of studies on the use of Terahertz (THz) imaging for contactless inspection of handwritten and possibly sealed documents as a preliminary study for the THz-based inspection of historical documents. We investigated the use of focused B-scans in transmission mode. As a basis, some general aspects associated with the investigated scenario are presented. These include investigations of paper and ink as well as the system’s image resolution. For possible application in scanning historical letters, one and stacks of two papers with handwriting inside an envelope were investigated. <

Continuous People Crowd Monitoring defined as a Regression Problem using Radar Networks - Guendel, Ronny G.; Ullmann, Ingrid; Fioranelli, Francesco; Yarovoy, Alexander (European Radar Conference, 2023)
Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a regression-based approach is used, which offers innovative insights into creating robust and accurate systems for monitoring human activities. Novel approaches utilizing LSTM or CNN regression techniques with Linear Regression and Support Vector Machine regressor are compared on extracted features from radar data through the Histogram of Oriented Gradients and Principal Component Analysis. These approaches are rigorously evaluated by a Leave-One-Group-Out method, with performance assessed using common regression metrics such as the RMSE. The most promising outcomes were observed for crowds of three and five individuals, with respective RMSE of approximately 0.4 and 0.6. These results were primarily achieved by utilizing the micro-Doppler (µD) Spectrogram or range-Doppler data domai

Data Compression for Close-Range Radar Imaging - Rückert, Rainer; Ullmann, Ingrid; Vossiek, Martin; Kaup, André; Herglotz, Christian (IEEE Transactions on Radar Systems, 2024)

Deep Learning Based Image Enhancement for Automotive Radar Trained with an Advanced Virtual Sensor - Schüßler, Christian; Hoffmann, Marcel; Ullmann, Ingrid; Ebelt, Randolf; Vossiek, Martin (IEEE Access, 2022)
This paper introduces a novel deep learning based concept for image enhancement and distortion suppression in automotive radar signal processing. The deep neural network (DNN) is trained solely on virtual data that is generated by an automotive MIMO radar ray tracing simulator. The simulator mimics the raw data that would be provided by a specific automotive MIMO radar for which the signal processing is envisaged. This virtual radar sensor, which has the same properties as the real radar, creates the DNN training input data. The unique feature of our approach is that an advanced virtual radar sensor is used to create the target values for the DNN training. The advanced virtual sensor is a simulated radar that works on the same basic principle as the real radar and its resembling virtual sensor, but is significantly upgraded in terms of performance. In our experiments the advanced virtual sensor, e.g., has a notably larger array, i.e., a much better lateral resolution, than the real radar. In addition, our advanced virtual sensor is not affected by multi-path effects, clutter, noise, beamforming sidelobes and other typical automotive radar distortions. The paper shows that a DNN trained on this advanced virtual sensor training data can deliver outstanding automotive radar signal processing results not only on simulated data but also on field data. The presented real-world automotive radar measurements show that multi-path, clutter and noise are efficiently suppressed by this DNN and that it has a remarkable ability to sharpen images and suppress sidelobes. The results presented in the paper suggest that the novel advanced DNN training concept based on virtual sensors offers opportunities that also go far beyond the radar signal processing capabilities illustrated. Hence, the concept put forward here is an attractive option for placing DNN-based radar signal processing on a novel and easy-to-implement foundation.<br
Keywords: Radar Imaging; Automotive Radar; Deep Neural Networks; Image Enhancement; Radar Simulation

Deep learning for terahertz image denoising in nondestructive historical document analysis - Dutta, Balaka; Root, Konstantin; Ullmann, Ingrid; Wagner, Fabian; Mayr, Martin; Seuret, Mathias; Thies, Mareike; Stromer, Daniel; Christlein, Vincent; Schür, Jan; Maier, Andreas; Huang, Yixing (Scientific Reports, 2022)
Historical documents contain essential information about the past, including places, people, or events. Many of these valuable cultural artifacts cannot be further examined due to aging or external influences, as they are too fragile to be opened or turned over, so their rich contents remain hidden. Terahertz (THz) imaging is a nondestructive 3D imaging technique that can be used to reveal the hidden contents without damaging the documents. As noise or imaging artifacts are predominantly present in reconstructed images processed by standard THz reconstruction algorithms, this work intends to improve THz image quality with deep learning. To overcome the data scarcity problem in training a supervised deep learning model, an unsupervised deep learning network (CycleGAN) is first applied to generate paired noisy THz images from clean images (clean images are generated by a handwriting generator). With such synthetic noisy-to-clean paired images, a supervised deep learning model using Pix2pixGAN is trained, which is effective to enhance real noisy THz images. After Pix2pixGAN denoising, 99% characters written on one-side of the Xuan paper can be clearly recognized, while 61% characters written on one-side of the standard paper are sufficiently recognized. The average perceptual indices of Pix2pixGAN processed images are 16,83, which is very close to the average perceptual index 16.19 of clean handwriting images. Our work has important value for THz-imaging-based nondestructive historical document analysis.<br
Keywords: Deep learning; Terahertz imaging; Historical document analysis; Nondestructive testing

Depth Camera Motion Tracking for Motion Compensation and ISAR Imaging in Walk-Through Security Scanners - Ullmann, Ingrid; Root, Konstantin; Vossiek, Martin (IEEE Journal of Microwaves, 2025)
This paper investigates the fusion of radar and depth camera for maintaining high-quality radar images in walk-through security scanners with significantly reduced array geometries. Therefore, after sensor calibration, the reconstruction volume is initially divided into sub-volumes and linked to the closest body part of a walking person being scanned. The depth camera's motion tracking provides the location and orientation of each body joint during the gait, allowing us to determine their trajectory and velocity. This information is then used to compensate for movement in the image reconstruction of each recorded radar frame. Afterwards, the motion compensated images are then superimposed to one ISAR image, considering the complete trajectory of the person. We conducted measurements with a 3.6GHz-to-10.6GHz walk-through security scanner and a real person carrying various objects. Motion tracking with a depth camera shows promising results for both imaging approaches. In the motion-compensated images, small details became visible and focused compared to reconstruction results without applied motion compensation. The ISAR approach demonstrated effective alignment of individual frames into one superimposed image, producing a full-body image even with a reduced array dimension. While these results prove the benefit of the fusion of radar and depth camera, further investigations into array design are necessary, as object visibility is strongly affected by the selected array geometry for ISAR imaging. This fact could complicate the reliable detection of potential threat objects with a downsized imaging arra
Keywords: Geometry; Tracking; Imaging; Radar; Radar imaging; Cameras; Radar tracking; Motion compensation; Security; Image reconstruction; ISAR; motion compensation; MIMO radar; personnel screening; radar imaging; security scanning

Improved Threat Detection in Walk-Through Security Scanning Using an Optimized Polarimetric Target Decomposition Method - Root, Konstantin; Adametz, Julian; Gumbmann, Frank; Ullmann, Ingrid; Vossiek, Martin (IEEE Journal of Microwaves, 2022)
Reliable and convenient walk-through security scanning, which doesn't separate people or impede their movement, is an extremely challenging task. In this paper, a novel approach for a security check with an overhead observation and a polarimetric target decomposition is presented. The viewing angle of the scanner equals a side-looking airborne radar. However, it will be shown that the established polarimetric target decomposition methods of remote-sensing are not well suited for close-range radar imaging and need to be adapted due to the differences in the geometry of the imaging scenario. The usage of a multiple input and multiple output (MIMO) array and the shorter distance between array and target need a changed decomposition technique in order to distinguish between persons with or without worn threat objects. The differences between radar remote-sensing and close-range imaging scenarios are investigated. An optimized version of the Sato four-component polarimetric scattering decomposition is derived. The proposed close-range adjustment is applied to the model and investigated experimentally with a 4-to-12 GHz fully polarimetric MIMO imaging system. Polarimetric decomposition is carried out on defined test structures with known scattering mechanisms, as well as on mannequins and persons with different threat objects like guns or explosives. In test campaigns, promising results were achieved for a correct target decomposition in radar-based walk-through security scanning.<br

Inverse Rendering of Near-Field mmWave MIMO Radar for Material Reconstruction - Hofmann, Nikolai; Wirth, Vanessa; Bräunig, Johanna; Ullmann, Ingrid; Vossiek, Martin; Weyrich, Tim; Stamminger, Marc (IEEE Journal of Microwaves, 2025)
Near-field multiple-input multiple-output (MIMO) radar systems allow for high-resolution spatial imaging by leveraging multiple antennas to transmit and receive signals across multiple perspectives. This capability is particularly advantageous in challenging environments, where optical imaging techniques struggle. We present a novel approach to inverse rendering for near-field MIMO radar systems, aimed at reconstructing material properties such as surface roughness, dielectric constants, and conductivity from radar and ground-truth mesh data, for example obtained from multi-view stereo. Drawing inspiration from physically based rendering techniques in computer graphics, we formalize an advanced inverse rendering algorithm that integrates electromagnetic wave propagation models directly into the optimization process. To avoid bias from conventional radar image reconstruction algorithms in the optimization process, we directly derive gradients from raw radar outputs, resulting in more accurate material characterization. We validate our approach through extensive experiments on both synthetic and real radar datasets, demonstrating its effectiveness in a multitude of scenario
Keywords: Backpropagation; MIMO radar; radar simulation; ray tracing; scattering parameters

In Vivo Skin-Type Classification Using Millimeter-Wave Near-Field Probe Spectroscopy - Hecht, Damaris; Pfahler, Tim; Ullmann, Ingrid; Altstidl, Thomas Robert; Amer, Nadia; Jin, Yi; Eskofier, Björn; Vossiek, Martin (2022 52nd European Microwave Conference, 2022)
This paper presents a methodology for millimeter-wave-based in vivo classification of human skin into the two naturally occurring skin types: thick skin with low water content and thin skin with high water content. For medical diagnostic applications in the microwave range, the distinction of the water content plays a major role. The method presented is based on the resonance characteristics of reflective skin measurements. Therefore, in vivo reflective spectra were measured on 10 individuals. For the measurement acquisition, a 3D printed rectangular waveguide-based near-field probe was designed that is sensitive to the skin water content in the frequency range of 75–110 GHz. In total, 360 reflection spectra were obtained, received from six different areas on the hands and arms of the volunteers. A support vector machine (SVM) model with two classes, thick skin on the palm and thin skin present on the arm and back of the hand, was trained with the measured data. The resulting SVM classifier was evaluated to have an accuracy of more than 95%. The high classification accuracy verifies the skin type classification approach as a simple and appropriate in vivo two-level hydration model for the human skin. On the basis of these results, complex challenges such as burn wound classification can become feasible, since ex vivo burn measurements have been shown to display equivalent resonant characteristics.<br

Kontaktlose, bildgebende Untersuchung historischer Dokumente im Terahertz-Frequenzbereich - Ullmann, Ingrid; Schür, Jan; Root, Konstantin; Vossiek, Martin (Jahrestagung der Deutschen Gesellschaft für Zerstörungsfreie Prüfung (DGZfP) 2022, 2022)
Bei der Untersuchung historischer Schriften ist es häufig nicht möglich oder erwünscht, die empfindlichen Dokumente zu öffnen, da das Risiko einer Beschädigung zu hoch ist. Zur kontaktlosen Inspektion solcher Dokumente kann die Röntgen-Technologie eingesetzt werden, allerdings einhergehend mit hohen Anforderungen an die Betriebssicherheit und einem potentiellen Beschädigungsrisiko für die zu untersuchenden Dokumente. Hier kann die Terahertz-Technologie eine interessante Alternative sein. Aufgrund der nicht-ionisierenden Strahlung und der geringen Leistungspegel gilt sie als unbedenklich, sowohl für Menschen als auch für historische Dokumente. Da Terahertz-Wellen die Eigenschaft besitzen, nichtleitfähige Materialien (u.a. Papier) zu durchdringen, besitzen Terahertz-Radarverfahren ein großes Potenzial zur berührungslosen und bildgebenden 3D-Darstellung von historischen Dokumenten. Im Gegensatz zum Seitenmaterial beinhalten historische Tinten häufig leitfähige oder stark verlustbehaftete Partikel, welche einen Bildkontrast zum Seitenmaterial bilden. Aufgrund der kurzen Wellenlängen sind mit Terahertz-Bildgebung Bildauflösungen im Sub-Millimeterbereich möglich. Die Terahertz-Technik wird daher bereits in vielfältigen Anwendungen im Bereich des Kulturerbes eingesetzt, beispielsweise zur Untersuchung historischer Gemälde. Die Untersuchung historischer Schriften mit Terahertz-Technologie ist dagegen noch ein relativ wenig beforschtes Gebiet. In diesem Beitrag werden verschiedene Mess- und Auswertemethodiken zur kontaktlosen Untersuchung historischer Dokumente mit Terahertz-Bildgebung vorgestellt und diskutiert: · Reflexions- und Transmissionsmessungen, · physikalische und synthetische Fokussierung, · Kurzpuls- und Dauerstrichverfahren. Der Beitrag zeigt aktuelle Forschungsergebnisse mit den verschiedenen Messmodalitäten. Im Fokus stehen zudem verschiedene Bildrekonstruktionstechniken. Die Eignung der Terahertz-Bildgebung zur Abbildung einlagiger und mehrlagiger Schriften wird diskutiert. Eine weitere Anwendung stellt die Abbildung historischer Schriftrollen dar, welche aufgrund der zylindrischen Objektgeometrie besondere Anforderungen an die Messgeometrie stellen. <

Magnetically Enhanced Ultrasound Strain Elastography to Visualize Magnetic Nanoparticles - Huber, Christian; Müller, Melina Sophie; Ermert, Helmut; Heim, Christian; Rupitsch, Stefan J.; Ullmann, Ingrid; Lyer, Stefan (22. GMA/ITG-Fachtagung Sensoren und Messsysteme 2024, 2024)
This study explores the potential of Magnetically Enhanced Ultrasound Strain Elastography (MUSE) for visualizing the distribution of magnetic nanoparticles (MNPs) employed in magnetic drug targeting (MDT). MDT leverages MNPs as drug carriers, accumulated by an external magnetic field at the target site, typically a tumor. The localized accumulation of these particles alters the effective elastic properties of the tissue, potentially enabling visualization through ultrasound strain imaging, which maps local variations in elasticity. However, a direct link between MNPs and regions of increased stiffness has yet to be established. This work proposes MUSE as a solution, utilizing an external magnetic field to manipulate MNP distribution and consequently, tissue elasticity. The feasibility of MUSE was assessed using a polyvinyl alcohol ultrasound phantom containing an MNP inclusion. The results demonstrated successful mapping of the inclusion using the proposed metho
Keywords: Medical Technology; Ultrasound Imaging; Cancer Therapy; Magnetic Nanoparticles; Magnetic Durg Targeting

Magnetomotive Displacement of Magnetic Nanoparticles in Different Tissue Phantoms - Huber, Christian; Heim, Christian; Li, Jiaqi; Ermert, Helmut; Rupitsch, Stefan J.; Ullmann, Ingrid; Lyer, Stefan (Current Directions in Biomedical Engineering, 2024)
Magnetic nanoparticles (MNPs) can be used invarious biomedical applications, such as magnetic drug tar-geting (MDT) or magnetic hyperthermia for cancer treatment.MNPs are injected into the body and accumulated with anexternal magnetic field at the tumor site. For therapy mon-itoring, the MNPs distribution has to be accurately mappedin real time. Magnetomotive ultrasound (MMUS) is a suit-able technique for this purpose. It was already demonstratedthat MMUS can map the accumulation process of MNPs dur-ing MDT. Moreover, inverse MMUS is an advanced techniqueto quantify MNP distribution. This method simulates the dis-placement of MNPs and surrounding tissues and compares theresults to measured data. Understanding how magnetomotivedisplacement behaves in various elastic environments is cru-cial for advancing inverse MMUS and accurately quantifyingMNP distributions. In this study, ultrasound tissue phantomswere fabricated with varying elastic parameters, incorporatingMNPs. Subsequently, their MMUS displacement is assesse
Keywords: Ultrasound Imaging; Displacement Tracking; Magnetic Nanoparticles; Magnetic Drug Targeting

Millimeter-wave imaging and near-field spectroscopy for burn wound assessment - Hecht, Damaris; Ullmann, Ingrid; Oppelt, Daniel; Pfahler, Tim; Amer, Nadia; Vossiek, Martin (Frequenz, 2022)
Diagnostic applications for skin in the microwave range have developed significantly in recent years, due the non-invasiveness of these applications and their ability to assess tissue water content. Despite their capabilities, however, there is still no appropriate clinically applicable microwave tool for the assessment of burn wounds. A common practice is the visual inspection and evaluation of burns by the doctor, which is a challenging task even for experienced medical professionals. An incorrect assessment can have far-reaching consequences, such as unnecessary surgery or surgery that is necessary but omitted. In this paper, two different approaches of millimeter-wave burn wound assessment are presented: millimeter-wave imaging and near-field spectroscopy. For imaging, a MIMO sparse array was used to assess ex vivo burns on porcine skin in the frequency range of 70-80 GHz. With a resonant millimeter-wave near-field probe, reflective spectroscopy at individual sites of an ex vivo burn on porcine skin in the frequency range of 75-110 GHz was performed. The results showed individual advantages and drawbacks for both approaches, with surprising benefits of the spectroscopic method. Nevertheless, both approaches were shown to be suitable for clinical usage in diagnosing burns.
CRIS-Team WoS Importer:2022-08-26
Keywords: burn injuries; millimeter-wave imaging; millimeter-wave spectroscopy; near-field probe; reflectometry

Millimeter-Wave Radar Image Reconstruction in Heterogeneous Media - Ullmann, Ingrid (47th European Microwave Conference (EuMC), Workshop on Short Range mmWave Imaging Systems, 2017)

Millimeter Wave Radar Imaging for Non-Destructive Detection of Material Defects - Ullmann, Ingrid; Adametz, Julian; Oppelt, Daniel; Vossiek, Martin (18th International Conference on Sensors and Measurement Technology (SENSOR 2017), 2017)

MIMO Radar-Based Rotation Parameter Estimation of Non-Cooperative Space Debris Objects - Kammel, Christoph; Ullmann, Ingrid; Vossiek, Martin (Proceedings of the IEEE Radar Conference, 2023)
This paper presents an approach to determine the rotation parameters of a non-cooperative space debris object by extracting, localizing and tracking the target's dominant scatterers with a millimeter-wave MIMO radar system. An unscented Kalman filter tracks the scatterer positions over several processing intervals and is therefore able to estimate the rotation period of the target as well as the position and orientation of its rotation axis. On the one hand, the proposed algorithm is validated by realistic simulations. On the other hand, the filter performance under different rotation parameters is evaluated by different measurements in the laboratory.
Created from Fastlane, Scopus look-up
Keywords: autonomous rendezvous; MIMO radar; space debris; unscented Kalman filter

Modelling and Construction of Complex Shaped Polyvinyl Alcohol based Ultrasound Phantoms for Inverse Magnetomotive Ultrasound Imaging - Heim, Christian; Huber, Christian; Ermert, Helmut; Ullmann, Ingrid; Saleem, Taimur; Lyer, Stefan; Rupitsch, Stefan Johann (22. GMA/ITG-Fachtagung Sensoren und Messsysteme 2024, 2024)
With regard to the application in local cancer treatment, the inverse magnetomotive ultrasound (IMMUS) modality needs to be extended to 3D on complex shaped polyvinyl alcohol (PVA) phantoms. Our four basic construction elements can be combined step-by-step to manufacture such complex shaped phantoms. The construction of complex shaped ultrasound phantoms requires the four basic elements (i) molds, (ii) scattering material, (iii) layering process, and (iv) mechanical coupling between different parts of the phantom. In this contribution, we describe the construction elements in detail to show the trade-offs between the possible shapes and positioning of the encapsulated volumes and the production time. Furthermore, since IMMUS requires knowledge of the mechanical parameters and the geometry of the target tumorous tissue, these parameters have to be determined during a magnetic drug targeting (MDT) therapy. The insertion of MDT therapy relevant amount of superparamagnetic iron oxide nanoparticles (SPIONs) does not significantly change the material properties. Therefore, quantitative ultrasound-based tissue characterization techniques (UTCT) such as shear wave elastography (SWE) or transient elastography (TE) can be used to characterize the target tumorous tissue once in advance of an MDT therapy. In this contribution, SWE and TE are exploited to determine shear wave velocity in PVA phantoms. Both methods show promising results for the determination of Young's modulu
Keywords: Magnetic Drug Targeting; Magnetic Nanoparticles; Magnetomotive Ultrasound Imaging; Polyvinyl Alcohol Ultrasound Phantom; Ultrasound-based Material Characterization

Motion Parameter Estimation of Free-Floating Space Debris Objects Based on MIMO Radar - Kammel, Christoph; Ullmann, Ingrid; Vossiek, Martin (IEEE Transactions on Radar Systems, 2023)
This paper presents a novel approach for estimating the motion parameters of noncooperative, free-floating space debris objects by assessing data from a multiple-input multiple-output radar system. The deployment of radar data renders the presented method particularly robust and reliable for use in the challenging space environment, with its frequently encountered harsh lighting conditions. The proposed algorithm initially extracts, locates, and tracks the dominant scatterers of the target by evaluating the range-Doppler diagrams derived from the radar data. Considering both the tracking results and a motion model, a cubature Kalman filter subsequently determines the rotational and translational motion parameters of the debris object, employing dual quaternions to describe its attitude and position. Thereby, the suggested method does not require prior information about the target object, such as its computer-aided design model, thus forming the basis for fully autonomous docking maneuvers and space debris removal. The algorithm was validated in a simulated space scenario and its performance simulatively assessed for small targets in the lower range of analyzability. Using an automated gimbal setup that realizes arbitrary controlled rotational movements, the proposed method was also practically tested in terms of achieved estimation errors and required convergence time. Finally, a comparison with a state-of-the-art unscented Kalman filter was performed to analyze the suitability of the chosen cubature Kalman filter approach.<br
Keywords: Quaternions; Radar; Spaceborne radar; Radar tracking; Target tracking; Space debris; Parameter estimation

Neuartige Konzepte für die Radarbildgebung in heterogenen Medien - Ullmann, Ingrid (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2021)

Non-destructive testing of arbitrarily shaped refractive objects with millimetre-wave synthetic aperture radar imaging - Ullmann, Ingrid; Adametz, Julian; Oppelt, Daniel; Benedikter, Andreas; Vossiek, Martin (Journal of Sensors and Sensor Systems, 2018)
Millimetre-wave (mmW) imaging is an emerging technique for non-destructive testing. Since many polymers are transparent in this frequency range, mmW imaging is an attractive means in the testing of polymer devices, and images of relatively high resolution are possible. This contribution presents an algorithm for the precise imaging of arbitrarily shaped dielectric objects. The reconstruction algorithm is capable of automatically detecting the object's contour, followed by a material-sensitive reconstruction of the object's interior. As an example we examined a polyethylene device with simulated material defects, which could be depicted precisel
lhft_intern.bib::Ullmann18b

Novel Chipless RFID Concept with High Data Capacity - Ullmann, Ingrid; Root, Konstantin; Vossiek, Martin (IEEE/MTT-S International Microwave Symposium (IMS), 2021)
We propose a new concept for passive RFID tags and an associated reading and decoding strategy. The information is encoded in the orientation of small wires inside the tag. A circular polarization millimeter-wave imaging system is used as an inter-rogation unit. Decoding is achieved by reconstructing a radar im-age of the tag and using the Hough transform to determine the wires’ orientations. We demonstrate the first-ever use of multi-layer image-based RFID tags. According to our results, up to four layers can be used. An information content of 251 bit (7 bit/cm2) was obtainable, which is unprecedented in image-based RFID. <

Polarimetric Decomposition Techniques for Short Range Imaging Radar - Adametz, Julian; Ullmann, Ingrid (International Microwave Symposium Workshop on Digital Signal Processing for Microwave Sensors and Imagers, 2019)

Radar-Based Continuous Human Activity Recognition with Multi-Label Classification - Ullmann, Ingrid; Guendel, Ronny G.; Kruse, Nicolas Christian; Fioranelli, Francesco; Yarovoy, Alexander (IEEE SENSORS, 2023)
This paper presents a novel approach to radar-based human activity recognition in continuous data streams. To date, most work in this research area has aimed at either classifying every single time step separately by means of recurrent neural networks, or using a two-step procedure of first segmenting the stream into single activities and then classifying the segment. The first approach is restricted to time-dependent data as input; the second approach depends crucially on the segmentation step. To overcome these issues we propose a new approach in which we first segment the stream into windows of fixed length and subsequently classify each segment. Since due to the fixed length, the segment is not restricted to one activity alone, we use a multi-label classification approach, which can account for multiple activities taking place in the same segment by giving multiple outputs. To obtain a higher classification accuracy we fuse several radar data representations, namely range-time, range-Doppler and spectrogram. Using a publicly available dataset, an overall classification accuracy of 95.8% and F1 score of 92.08% could be achieved with the proposed metho
Keywords: continuous human activity recognition; radar; multi-label classification; deep learning; ResNet; activities of daily living

SAR Based Non-Destructive Evaluation of Irregularly Shaped Objects with Simultaneous Estimation of Geometry and Permittivity - Ullmann, Ingrid; Adametz, Julian; Vossiek, Martin (16th European Radar Conference (EuRAD 2019), 2019)
The geometrically correct registration of subsurface structures that are embedded in a medium with unknown shape and permittivity - e.g. a small defect in fiber or ceramic components - is one of the most challenging tasks in radar imaging. This paper presents a new methodology for subsurface synthetic aperture radar (SAR) imaging with integrated estimation of geometry and permittivity applicable for non-destructive evaluation (NDE). Two SAR measurements are performed, one scanning the device under test (DUT) from the front side, the second scanning the DUT from the backside. By comparing the contour profile derived from the front side/ backside measurement with an SAR image of the complete DUT reconstructed under the assumption of free-space propagation, the permittivity and complete contour of the DUT are estimated. A high-resolution image is then reconstructed with an adapted subsurface backprojection algorithm that considers the contour and permittivity estimates correctly. Experimental results with a polyethylene DUT with two small embedded defects are presented that validate the proposed technique. It is shown that with the novel approach good estimations of shape and permittivity as well as geometrically correct high resolution images can be achieved

Taking a Look Beneath the Surface: Multicopter UAV-Based Ground-Penetrating Imaging Radars - Grathwohl, Alexander; Stelzig, Michael; Kanz, Julian; Fenske, Patrick; Benedikter, Andreas; Knill, Christina; Ullmann, Ingrid; Hajnsek, Irena; Moreira, Alberto; Krieger, Gerhard; Vossiek, Martin; Waldschmidt, Christian (IEEE Microwave Magazine, 2022)
The field of multicopter unmanned aerial vehicles (UAVs) has seen massive technological advances and decreasing costs over the last decade. Due to the higher prevalence and availability of these multicopter UAVs, there have also been rapid improvements in the software interfaceability, enabling the easy integration of custom software for flight planning and controllers. This opened up completely new possibilities, such as low-cost individual aerial photography, the most common civilian application. Furthermore, lightweight multicopters became widely accessible to the public, boosting the development of UAVs even more.<br

Terahertz Synthetic Aperture Radar Imaging of Thermal Barrier Coatings on Metal Substrates - Ullmann, Ingrid; Oppelt, Daniel; Adametz, Julian; Schür, Jan; Vossiek, Martin (8th International Workshop on Terahertz Technology and Applications, 2018)
lhft_intern.bib::Ullmann18a

Towards Continuous Real-Time Plant and Insect Monitoring by Miniaturized THz Systems - Sheikh, Fawad; Prokscha, Andreas; Batra, Aman; Lessy, Dien; Salah, Baha; Sievert, Benedikt; Degen, Marvin; Rennings, Andreas; Jalali, Mandana; Svejda, Jan Taro; Alibeigloo, Pooya; Preuss, Christian; et al. (IEEE Journal of Microwaves, 2023)
In this paper, new concepts for continuous 24/7 real-time monitoring of plants and insects with miniaturized terahertz (THz) systems are described and experimentally tested. Thus, for the first time, small-scale insights into the instantaneous plant health but also in their long-term growth can be obtained. Using such compact THz systems, e.g. water uptake, insect infestation and the behavior of pollinators (i.e. honey bees) and pests can be measured dynamically and non-invasively at virtually any position in the close biotope surrounding them. In addition to general understanding, this can be used to optimize crop yield and reduce resource consumption as well as for identifying characteristics of insect-plant interactions induced by potential environmental stressors. Given such a holistic approach, the proposed concepts may provide a significant advancement in environmental monitoring technology.<br
Keywords: Insects; Monitoring; Temperature measurement; Biomedical monitoring; Temperature sensors; Detectors; Real-time systems

Towards Detecting Climate Change Effects With UAV-Borne Imaging Radars - Ullmann, Ingrid; Bonfert, Christina; Grathwohl, Alexander; Lahmeri, Mohamed Amine; Mustieles Perez, Victor; Kanz, Julian; Sterk, Elena; Bormuth, Frederik; Ghasemi, Roghayeh; Fenske, Patrick; Villano, Michelangelo; Schober, Robert; et al. (IEEE Journal of Microwaves, 2024)
Climate change is associated with a variety of environmental phenomena, such as the melting of glaciers, the drying out of crops and soils, and an increase in the risk of avalanches. To detect and monitor these changes, satellite-based radar imaging is widely used, as it enables the large-scale mapping of the Earth's surface independent of weather and sunlight. An emerging field of research is to use radar systems mounted on unmanned aerial vehicles (UAVs) for this purpose. UAV-borne radar systems image smaller areas, but can capture them in greater detail, more flexibly in terms of flight trajectory, and at shorter repetition intervals. This article presents the capabilities of UAV-based radar systems and the associated challenges in terms of system design and imaging techniques for detecting and monitoring the effects of climate change. Current research results are shown. In addition, we give an outlook on using a swarm of cooperative UAVs, each carrying a radar. UAV swarms will enable a higher imaging quality with respect to resolution and detectability, but at the same time come with a number of additional challenges, which will be discussed in the paper as well.
CRIS-Team Scopus Importer:2024-09-27
Keywords: Climate change; microwaves in climate change; radar; radar imaging; remote sensing; UAV

Two-Component Scattering Decomposition Technique for Walk-Through Security Scanners Using a Copolarized-MIMO Array - Root, Konstantin; Ullmann, Ingrid; Vossiek, Martin (2024 21st European Radar Conference, EuRAD 2024, 2024)
The widespread deployment of walk-through security scanners necessitates high reliability and a minimal false-alarm rate. This paper proposes a novel approach to improve existing systems by distinguishing between two scattering processes encountered during security checks: reflections from skin versus reflections from concealed objects. As skin shows specular reflection behavior, whereas objects tend to reflect diffuse, reconstruction results of the same scene with different array geometries show different imaging results. Therefore, we separate the imaging array into multiple partial arrays that exploit this scattering behavior beneficially. After obtaining the different reconstruction images, we propose an image processing technique that allows to obtain information about object reflections in the scene. This technique uses existing state-of-the-art walk-through scanners without the need for hardware modifications and hence, can easily be integrated. We validate the efficiency of this approach through realistic measurements involving human subjects and various threat objects. Our results demonstrate the capability to detect these objects, offering promise to improve existing systems.
CRIS-Team Scopus Importer:2024-12-13
Keywords: MIMO radar; personnel screening; radar imaging; scattering decomposition; security scanning

Ultrahigh-Performance Radio Frequency System-on-Chip Implementation of a Kalman Filter-Based High-Precision Time and Frequency Synchronization for Networked Integrated Sensing and Communication Systems - Ghasemi, Roghayeh; Fenske, Patrick; Kögel, Tobias; Hehn, Markus; Ullmann, Ingrid; Vossiek, Martin (IEEE Open Journal of Instrumentation and Measurement, 2025)
The integration of radar sensing and imaging capabilities into future integrated sensing and communication (ISAC) networks enables advanced use cases, including autonomous vehicle navigation, real-time health monitoring, and smart city management. However, ultraprecise time and frequency synchronization is crucial for unlocking the full potential of such networked ISAC systems. In this article, a novel real-time wireless time and frequency synchronization scheme is developed and fully implemented on a high-end radio frequency system-on-chip field-programmable gate array (FPGA) platform. The excellent performance and robustness of the proposed solution in practical applications are demonstrated. It is evidenced that the recursive nature of the Kalman filter is well suited to the dynamic capabilities of FPGA-based simultaneous synchronization. Observed values obtained through the precision time protocol (PTP) are iteratively refined, thus effectively compensating for uncertainties encountered during a synchronization packet exchange. Due to the deterministic processing time inherent in the FPGA, the proposed synchronization method achieves exceptional precision, with clock offset deviations in the nanosecond range and clock rate deviations limited to only a few parts per billion, even across considerable distances between the network node
CRIS-Team Scopus Importer:2025-01-31
Keywords: Synchronization; Clocks; Time-frequency analysis; Frequency synchronization; Kalman filters; Sensors; Protocols; Frequency estimation; Wireless sensor networks; Real-time systems

Ultrasound-based Eigenfrequency Analysis to Determine Material Parameters of Tissue Mimicking Phantoms - Heim, Christian; Huber, Christian; Ullmann, Ingrid; Lyer, Stefan; Rupitsch, Stefan J. (Current Directions in Biomedical Engineering, 2024)
A modern area of research in cancer treatment is magnetic drug targeting (MDT) with superparamagnetic iron oxide nanoparticles (SPIONs). In order to understand the processes involved in MDT in more detail and to be able to perform this therapy as efficientlyas possible, a monitoring system for thespatialdistribution of SPIONs in biological tissue is required. One approach is to use magnetomotive ultrasound (MMUS) to monitorthe spatial distribution over time. However, the spatial distributionof SPIONs cannot be quantitatively determined applyingbasic MMUS algorithms. Therefore, MMUS has been extended bya simulation part to quantitatively determine the spatial distributionof SPIONs. This extendedMMUS algorithm requires the material parametersand the geometry of the target tumorous tissue. In this contribution,we describe anultrasound-based eigenfrequency analysiscombined with an iterative inverse simulation-based methodto determine the mechanical parameterYoung's modulus oftissue mimicking phantoms.The presentedapproachyields a goodestimate of the Young's modulus compared to the result fromacompression tes
Keywords: Magnetic Drug Targeting; Magnetic Nanoparticles; EigenfrequencyAnalysis; Ultrasonic Sensing; Polyvinyl AlcoholPhantom

Ultrasound-Induced Stable and Inertial Cavitation of Magnetic Nanoparticles for Drug Delivery Applications - Huber, Christian; Hageroth, Lars; Meyer, Constanze; Ermert, Helmut; Ullmann, Ingrid; Vossiek, Martin; Lyer, Stefan (Current Directions in Biomedical Engineering, 2024)
Drug-loaded magnetic nanoparticles (MNPs) ac-cumulated by an external magnetic field already showed theirefficacy in localized tumor treatment in animal studies. Fur-thermore, specific MNPs are sonosensitive, enabling them togenerate inertial cavitation when exposed to a focused ultra-sound field. This can be used for controlling drug release, aswell as for particle detection and mapping. In addition to in-ertial cavitation, stable cavitation is also a part of the cavi-tation process, which has not yet been evaluated on MNPs.While stable cavitation is less harmful to surrounding tissuecompared to inertial cavitation, it also contributes to enhancedtumor perfusion. Hence, an optimal strategy could involve in-ducing inertial cavitation only within the tumor region for drugrelease and mapping, while employing stable cavitation out-side the tumor to enhance perfusion. This study aims to inves-tigate stable cavitation mediated by MNPs for the first time,while examining their overall cavitation behavio

Ultrasound-Mediated Cavitation of Magnetic Nanoparticles for Drug Delivery Applications - Huber, Christian; George, Benedikt; Rupitsch, Stefan Johann; Ermert, Helmut; Ullmann, Ingrid; Vossiek, Martin; Lyer, Stefan (Current Directions in Biomedical Engineering, 2022)
Magnetic nanoparticles guided by an external magnetic field can be used to deliver drugs (e.g., chemotherapeutics) to malignant regions (e.g., tumor tissue). Some nonmagnetic, sonosensitive nanoparticles are known to generate cavitation induced by focused ultrasound. This can can be used to monitor spatial/temporal particle distribution and to stimulate local drug release in target regions. Little to nothing is known about the sonosensitivity of magnetic nanoparticles. Therefore, we investigated this physical phenomenon in the present contribution. We showed that certain magnetic nanoparticles have high cavitation potential and are promising for further research in this regard.
CRIS-Team Scopus Importer:2023-03-08
Keywords: Cavitation; Drug Delivery; Magnetic Nanoparticles; Sonosensitivity; Ultrasound

Ultrasound Phantom of a Carotid Bifurcation Tumor Using Multiple 3D Printed Soluble Filaments - Huber, Christian; Heim, Christian; Ermert, Helmut; Rupitsch, Stefan Johann; Ullmann, Ingrid; Vossiek, Martin; Lyer, Stefan (2024 IEEE International Symposium on Biomedical Imaging (ISBI), 2024)
Accurate models of biological structures are essential for medical training, calibrating equipment, and advancing research without animal experiments. In ultrasound, tissue mimicking phantoms, using materials like agarose or gelatin with added scatterers, are commonly used to simulate biological tissue. While the properties of these phantoms are integral for faithful ultrasound environments, their inner and outer structures are equally crucial. Modifying the outer structure is straightforward with outer molds, but altering the inner structure presents greater challenges. Introducing a tumor structure typically involved using either cylindrical or tethered spherical inclusions, both of which can introduce unwanted reflections. The incorporation of flow systems typically relies on removable rods, limiting complexity. Using 3D printed soluble filament, dissolved in multiple steps, helps to create nearly arbitrary inner structures with different tissue mimicking materials. In this study, the process of generating such complex ultrasound phantoms is described and evaluated with ultrasound measurement

Visualization of Magnetic Nanoparticles by Ultrasound Strain Imaging - Huber, Christian; El Aawar, Karim; Ullmann, Ingrid; Lyer, Stefan; Ermert, Helmut (SMSI 2023 Conference – Sensor and Measurement Science International, 2023)
In magnetic drug targeting, superparamagnetic nanoparticles are used as drug carriers. The local accumulation of these particles at the site of the tumor leads to a temporary change in the effective elastic tissue properties in this area. Therefore, mapping this change should allow visualization of the particle distribution. Ultrasound strain imaging is a method to map the local variation of elasticity. This method was tested using a polyvinyl alcohol ultrasound phantom with a magnetic nanoparticle inclusion. It was demonstrated, that this inclusion can be mapped in the proposed wa
Keywords: Ultraschallbildgebung; Ultraschallelastographie; Magnetische Nanopartikel; Magnetic Drug Targeting

Wall-less Flow Phantoms with 3D printed Soluble Filament for Ultrasonic Experiments - Huber, Christian; Lyer, Stefan; Ermert, Helmut; Heim, Christian; Rupitsch, Stefan J.; Ullmann, Ingrid (Current Directions in Biomedical Engineering, 2023)
Tissue-mimicking materials (TMMs) typically used for ultrasound phantoms include gelatin, agarose and polyvinyl alcohol (PVA). These materials have shown sufficient similarity in ultrasound parameters compared to human tissue. Despite their extensive use for years to generate ultrasound phantoms, no simple and easily reproducible way to generate complex, wall-less ultrasound flow phantoms has been introduced. Commercially available ultrasound flow phantoms are limited to simple flow geometries that do not reflect the complex blood flow in humans. Flow phantoms with complex geometries presented in scientific publications either have walls between TMMs and the flow channel, are limited to one material, or are complicated to produce. In this contribution, we present a method using 3D printing and soluble filament that allows for the reliable and consistent production of complex flow geometries with the typical materials used for ultrasound phantoms and without any walls.
CRIS-Team Scopus Importer:2023-10-20
Keywords: 3D Printing; Flow Experiments; Ultrasound; Ultrasound Phantoms

Water-soluble filament in multifilament approach for ultrasound phantom fabrication - Huber, Christian; Lahmadi, Wahbi; Alballa, Ahmad; Heim, Christian; Rupitsch, Stefan J.; Ermert, Helmut; Ullmann, Ingrid; Lyer, Stefan (Transactions on Additive Manufacturing Meets Medicine, 2024)
Ultrasound phantoms are used in research, equipment testing, calibration, and even in the field of medical training. Despite their importance, commercial ultrasound phantoms are often expensive and may not meet user requirements. While simplistic phantom construction methods exist which use readily available materials, they often lack versatility in both their exterior and interior designs. By using tissue-mimicking materials such as gelatin, agarose, or polyvinyl alcohol mixed with water, simple yet effective ultrasound phantoms can be created through a heating and hardening process. While designing the outer structure of these phantoms can be achieved through the creation of various molds, crafting complex inner structures poses a more difficult task. Additive manufacturing, specifically fused deposition printing with standard 3D printers, presents a promising solution to this challenge. This involves using soluble materials that can be removed after the phantom hardens. In prior research, we successfully demonstrated this methodology using high impact polystyrene and VXL70. Building on this, our current study aims to simplify the process and evaluate non-toxic, water-soluble filaments. Using polyvinyl alcohol filament in combination with high impact polystyrene is a promising approach. These phantoms serve versatile purposes, including the replication of vascular structures or the incorporation of distinct material regions to simulate tumor structures. Through this investigation, we aim to enhance the accessibility and functionality of ultrasound phantoms for diverse research and medical applications.<br