A Dual-polarized UWB Antenna System for the Demonstration of Autonomous Localization and Object Recognition with Mobile Sensors - Deißler, Tobias; et al. (Proceedings of International Workshop on Antenna Technology (iWAT), 2012)
UnivIS-Import:2015-04-16:Pub.2012.tech.IE.komele.adualp

Cooperative Localization and Object Recognition in Autonomous UWB Sensor Networks - Deißler, Tobias; Thielecke, Jörn; Zetik, Rudolf; Yan, Honghui; Malz, Elke; Jovanoska, Snezhana; Shen, Guowei; Thomä, Reiner; Salman, Rahmi; Schultze, Thorsten; Tobera, Robert; Willms, Hans-Ingolf; et al. (Ultra-Wideband Radio Technologies for Communications, Localization and Sensor Applications, 2013)
UnivIS-Import:2015-04-20:Pub.2013.tech.IE.komele.cooper

Feature Based Indoor Mapping Using a Bat-Type UWB Radar - Deißler, Tobias; Thielecke, Jörn (Feature Based Indoor Mapping Using a Bat-Type UWB Radar, 2009)
A system for building a feature-based map of an unknown indoor environment is proposed. We consider emergency scenarios where smoke and dust block the vision so that camera-based systems and laser range finders are not operable. In this kind of situation, ultra-wideband (UWB) radar is a good alternative. We use a bat-type UWB radar system composed of one transmitter and two receivers arranged in a fixed linear array. Time-of-flight measurements are taken between the transmitter and the receivers. The environment is reconstructed from impulse responses by extracting information on different features like walls, edges and corners. These features can be used as landmarks to navigate. The solution we present works by dividing the problem into three different parts and solving them: Tracking of the bat pose and localization of already detected landmarks; data association to single out measurements originating from the detected landmarks; and detection of new landmarks from the remaining measurements. By combining solutions to these three subtasks, a computationally cheap, precise algorithm for feature-based indoor mapping is obtained. Tests using real life data were performed to confirm the feasibility of the approach. © 2009 IEEE.
UnivIS-Import:2015-04-16:Pub.2009.tech.IE.komele.featur
Keywords: Feature extraction; Localization; Radar; SLAM; Ultra-wideband

Fusing odometry and sparse UWB radar measurements for indoor slam - Thielecke, Jörn; Deißler, Tobias (8th Workshop on Sensor Data Fusion: Trends, Solutions, Applications, SDF 2013, 2013)
For security applications and in situations where optical sensors are not working, ultra-wideband (UWB) radar is an alternative technology for localization, mapping and object recognition. This paper presents an approach for solving the simultaneous localization and mapping (SLAM) problem for an autonomous robot with a small UWB radar array. Feature-based mapping in conjunction with an underlying state space model enables the reconstruction of the room with accuracy up to 10 cm. Two different ways of dealing with the data association problem - the task of sorting the measured time-of-flight values - are presented. Data fusion with odometry information is proposed to reduce the number of measurement steps. Experimental results with an autonomous robot show the feasibility of the concept. © 2013 IEEE.
UnivIS-Import:2015-04-16:Pub.2013.tech.IE.komele.fusing
Keywords: Data fusion; Indoor navigation; Odometry; UWB mapping

Infrastructureless Indoor Mapping Using a Mobile Antenna Array - Deißler, Tobias; Thielecke, Jörn; Malgorzata, Janson; Zetik, Rudolf (Proceedings of 19th International Conference on Systems, Signals and Image Processing (IWSSIP), 2012, 2012)
In environments where optical sensors are not working or not sufficient, ultra-wideband (UWB) radar is an alternative technology for localization, mapping and object recognition. This paper presents an approach for indoor map building using an UWB radar and a simple mobile antenna array with one transmitter and two receivers. It requires no a priori knowledge of the surrounding and no additional infrastructure. A feature based approach with an underlying state space model is used. The data association problem is solved by grouping in the measurement space. Tests with simulated and measured data show that an accuracy up to 10cm can be achieved so far. © 2012 Institute of Telecommunica.
UnivIS-Import:2015-04-16:Pub.2012.tech.IE.komele.infras
Keywords: indoor navigation; mapping; UWB

Navigation und Lokalisierung - Deißler, Tobias; Michal, Pietrzyk (Lehre und Forschung am Lehrstuhl für Informationstechnik, 2009)
UnivIS-Import:2015-04-20:Pub.2009.tech.IE.komele.naviga_9

UWB Feature Localization for Imaging - Seitz, Jochen; Schaub, Markus; Hirsch, Ole; Zetik, Rudolf; Deißler, Tobias; Thomä, Reiner; Thielecke, Jörn (UWB Feature Localization for Imaging, 2008)
Object recognition, localization and imaging capabilities of ultra-wideband signals are demonstrated in this contribution. Resembling a bat, the experimental setup comprises one transmitter and two receivers. Instead of ultrasound, electromagnetic ultra-wideband (UWB) signals are used to recognize and localize features of the surroundings like e.g. walls, edges or corners. Each feature corresponds to a hypothesis on the dominant reflection and scattering conditions described in terms of simple ray-tracing relationships. The hypothesis matching best the propagation time measurements is picked to identify and localize the feature in front of the moving UWB bat. Henceforth these features could be used as landmarks for bat navigation. Both, position and attitude of the UWB bat could be continuously updated based on a map of landmarks. This kind of navigation is well-known in the literature as simultaneous localization and mapping. Since position and attitude of the UWB bat are tracked, an image of the vicinity in front of the UWB bat can be compiled by superimposing the impulse responses recorded at the various locations. This contribution describes the pivotal elements to this approach: feature recognition and localization as well as bat-type imaging. ©2008 IEEE.
UnivIS-Import:2015-04-16:Pub.2008.tech.IE.komele.uwbfea
Keywords: Feature extraction; Imaging; Localization; Ultra wide band

UWB Radar Object Recognition for SLAM - Deißler, Tobias; Thielecke, Jörn; Salman, Rahmi; Schulze, Thorsten; Willms, Hans-Ingolf (Proceedings of 11th International Radar Symposium, 2010)
In situations where the environment is filled with dust or smoke, like in many emergency scenarios, UWB Radar is a possible technology to still sense the surrounding and build maps, thus helping firemen and other rescue personal. In this paper, a combination of two algorithms is presented. A basic simultaneous localization and mapping (SLAM) algorithm relying on simple indoor features is used to explore the environment and build a map. This algorithm is augmented by an object-recognition (OR) algorithm that is capable of recognizing and localizing complex shapes. These shapes can be used to improve the map resolution accuracy and resolve ambiguities. First tests using an m-sequence UWB Radar indicate the feasibility of this concept.
UnivIS-Import:2015-04-16:Pub.2010.tech.IE.komele.uwbrad
Keywords: Emergency services; Mapping; Object recognition; SLAM; UWB

UWB SLAM with Rao-Blackwellized Monte Carlo Data Association - Deißler, Tobias; Thielecke, Jörn (Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2010, 2010)
In situations where the environment is filled with dust or smoke, like in many emergency scenarios, it is still possible to sense the surrounding and build maps by using ultra-wideband (UWB) Radar. This can help firemen and other rescue personnel. In this paper, a method to solve the SLAM (simultaneous localization and mapping) problem is presented. Using UWB radar with a bat-type antenna array consisting of two RX antennas and one TX antenna in the middle, features of the surroundings are detected and used as landmarks for navigation. The main challenge of this approach is the problem of data association, i.e. the task of assigning time-of-flight measurements to corresponding landmarks. The solution presented in this article uses a state space model in combination with a Rao-Blackwellized particle filter. © 2010 IEEE.
UnivIS-Import:2015-04-16:Pub.2010.tech.IE.komele.uwbsla
Keywords: Indoor navigation; SLAM; UWB