Simulation and experimental study demonstrates enhanced pedestrian detection across inhomogeneous clutter, highlighting improved reliability for automotive FMCW radar.
Pedestrian detection is a crucial aspect in the application of linear frequency-modulated continuous-wave (FMCW) radar systems. A high-resolution FMCW radar can detect the micro-Doppler distribution reflected by a walking person from different body parts. Therefore, the pedestrian has a spread Doppler spectrum, known as the Doppler-spread target (DST). Existing constant false alarm rate (CFAR) methods still have missed detection when detecting DSTs. Moreover, the adaptability of detector in different clutter environments is often ignored. To improve the detection probability of DSTs while maintaining stable detection performance in inhomogeneous clutter environments, a DST summation variability index CFAR (DST-SVI-CFAR) detector is proposed, which builds detection cells by accumulating power cells of DST and calculates the threshold based on the distribution model of DST. The VI-CFAR is combined for strategy selection. When calculating the threshold, the expressions for the associated threshold factor and false alarm probability are derived to calculate the threshold factor. Through simulation analysis, it is confirmed that the proposed method improves detection performance and performs robustly in clutter environments. Additionally, practical test results also demonstrate that the DST-SVI-CFAR detector exhibits a higher detection probability compared to other CFAR methods.
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Zhao et al. (2024) studied this question.
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