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

Multiple Target Measurements: Bayesian Framework for Moving Object Detection in Mimo Radar - Eisele, Bastian; Bereyhi, Ali; Müller, Ralf (ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023)
Utilizing compressive sensing (CS), one can significantly reduce the number of required antenna elements in MIMO radar systems, while preserving a high spatial resolution. Most CS-based studies focus on individual processing of a single set of measurements collected from an stationary scene. In this paper, we propose a new scheme called multiple target measurements (MTM). This scheme uses the target movement to collect multiple sets of measurements from jointly sparse stationary scenes. Invoking approximate message passing, we develop a Bayesian-like iterative algorithm to recover the sparse scenes jointly. Our analytical and numerical investigations demonstrate that MTM can further reduce the array size required to achieve a desired spatial resolutio
Keywords: Compressive Sensing; MIMO Radar; Approximate Message Passing

Vector Approximate Message Passing for 3D MIMO Radar - Eisele, Bastian; Bereyhi, Ali; Müller, Ralf; Rangan, Sundeep (Asilomar Conference on Signals, Systems, and Computers, 2024)