Ultra-Wideband Radar Detection Based on Target Response and Time Reversal

• Published in: IEEE sensors journal Vol. 24; no. 9; pp. 14750 - 14762
• Main Authors: Li, Yajun, Xu, Lin, Wang, Pengfei, Ding, Baogang, Zhao, Suqiang, Wang, Zhicheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Clutter; Detectors; Energy distribution; Likelihood ratio; Monte Carlo simulation; Multiple scatter; Object detection; Radar; Radar detection; Radar targets; Scattering; Sensors; Target detection; time frequency (TF); time reversal (TR); Time-frequency analysis; ultra-wideband (UWB) radar; Ultrawideband radar
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2024.3376696

Target detection based on time reversal (TR) effectively uses multipath effects to achieve the space-time focusing effect and enhance radar detection performance by adaptively matching the propagation channel. In the context of ultra-wideband (UWB) radar applications, detection targets are often considered as extended targets comprised of multiple scattering points. The echoes from these scattering points carry rich information about the target's characteristics, and thus the target's response cannot be ignored. In this article, considering the target's response characteristics, a single-station radar target detection method combining TR and time-frequency (TF) analysis algorithms is proposed for complex environments characterized by clutter, multipath signals, and target responses. In the conventional TR algorithm, we incorporate TF analysis and optimize the energy distribution of the time-reversed transmission signal by comprehensively analyzing the TF domain information of the target echo signals. Consequently, we propose a TR and TF likelihood ratio test (TFTR-LRT) detector that leverages target response characteristics to improve detection probability. In addition, we compare the proposed detector with several conventional detectors under the same conditions. Theoretical derivations and Monte Carlo simulation results demonstrate that the TFTR-LRT detector significantly outperforms other detectors in a mixed environment of clutter, multipath signals, and target responses.