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Target detection based on time reversal 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 can not be ignored. In this paper, considering the target's response characteristics, a single-station radar target detection method combining time-reversal (TR) and time-frequency (TF) analysis algorithms is proposed for complex environments characterized by clutter, multipath signals, and target responses. In the conventional time-reversal algorithm, we incorporate time-frequency analysis and optimize the energy distribution of the time-reversed transmission signal by comprehensively analyzing the time-frequency domain information of the target echo signals. Consequently, we propose a time-reversal and time-frequency 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.
Li et al. (Tue,) studied this question.
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