Improved Clutter Suppression and Detection of Moving Target with a Fully Polarimetric Radar

Remote sensing of moving targets, particularly pedestrians on the road, is crucial for advanced driver assistance systems. However, pedestrian detection using the radar system remains an ongoing challenge due to the radar cross section (RCS) of pedestrians being much smaller than that of the clutter. Existing radar systems and pedestrian detection methods predominantly rely on the single-polarization radar, while research on the fully polarized radar for pedestrian detection is relatively limited. In this paper, the L-band fully polarimetric radar system is developed for pedestrian detection, and based on the full polarized radar echo HH, HV, VH, and VV, a novel clutter suppression method is proposed, which integrates the optimal polarization states of antennas and optimal scattering characteristics of pedestrians. Moreover, the field experiment has been conducted, and the results demonstrate that the signal-to-clutter-plus-noise ratio (SCNR) of the total power signal of full-polarization echoes is higher than that of single-polarization echoes, and the proposed clutter suppression method is able to reduce the non-stationary clutter and the interference signal generated by the multipath effect, thereby improving the SCNR. Furthermore, the OTSU algorithm is employed to detect pedestrian targets using radar data before and after clutter suppression, and the results demonstrate that the proposed method yields superior detection performance. These findings justify the potential of fully polarimetric radar in enhancing pedestrian detection.

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Publication Details

Journal
Remote Sensing
Published
2025-08-27
DOI
https://doi.org/10.3390/rs17172975
Citations
3
Primary Topic
Radar Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
14.98

Funders

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article

Improved Clutter Suppression and Detection of Moving Target with a Fully Polarimetric Radar

Xin Liu, Changhu Xue, Zongqiang Liu, Zhongkai Wen et al.
3 citations
Remote Sensing
Radar Systems and Signal Processing
14.98
article

Improved Clutter Suppression and Detection of Moving Target with a Fully Polarimetric Radar

Xin Liu, Changhu Xue, Zongqiang Liu, Zhongkai Wen, Zhiying Cui, Yaxin Mu, Zhenghuan Xia, Haibin Zhu, Zhilong Zhao, Xutao Hou
article en
3 citations

Abstract

Remote sensing of moving targets, particularly pedestrians on the road, is crucial for advanced driver assistance systems. However, pedestrian detection using the radar system remains an ongoing challenge due to the radar cross section (RCS) of pedestrians being much smaller than that of the clutter. Existing radar systems and pedestrian detection methods predominantly rely on the single-polarization radar, while research on the fully polarized radar for pedestrian detection is relatively limited. In this paper, the L-band fully polarimetric radar system is developed for pedestrian detection, and based on the full polarized radar echo HH, HV, VH, and VV, a novel clutter suppression method is proposed, which integrates the optimal polarization states of antennas and optimal scattering characteristics of pedestrians. Moreover, the field experiment has been conducted, and the results demonstrate that the signal-to-clutter-plus-noise ratio (SCNR) of the total power signal of full-polarization echoes is higher than that of single-polarization echoes, and the proposed clutter suppression method is able to reduce the non-stationary clutter and the interference signal generated by the multipath effect, thereby improving the SCNR. Furthermore, the OTSU algorithm is employed to detect pedestrian targets using radar data before and after clutter suppression, and the results demonstrate that the proposed method yields superior detection performance. These findings justify the potential of fully polarimetric radar in enhancing pedestrian detection.

Remote SensingVol. 17(17)
China Academy of Space Technology (CN), Space Engineering University (CN), Beijing Information Science & Technology University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Radar Systems and Signal Processing
14.98
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