TY - JOUR
T1 - BeiDou-Based Passive Multistatic Radar Maritime Moving Target Detection Technique via Space-Time Hybrid Integration Processing
AU - Li, Zhongyu
AU - Huang, Chuan
AU - Sun, Zhichao
AU - An, Hongyang
AU - Wu, Junjie
AU - Yang, Jianyu
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2022
Y1 - 2022
N2 - This article puts forward a BeiDou-based passive multistatic radar (PMR) maritime moving target (MMT) detection technique via space-time hybrid integration (STHI) processing. Compared with passive bistatic radar (PBR), the utilization of multiple satellites provides an improvement in MMT detection performance, together with the capabilities of localization and velocity estimation. However, the multiple satellite transmitters cause the differences principally in bistatic range and Doppler centroid (DC) of the MMT. To integrate the PMR echoes, the biggest challenge is the two differences that need to be handled. In the proposed technique, first, the centroid-compensated keystone transform (CCKT) is proposed and applied to each PBR echo. It not only corrects range cell migration (RCM) but also equalizes the DC to the same. Then, the long-time integration is performed on each PBR echo, after which it is integrated into the range-Doppler frequency rate (DFR) domain. Finally, in order to settle the difference in bistatic range, an MMT position and velocity domain (i.e., the X - Y - V domain) is constituted. The obtained multiple range-DFR maps are projected to the X - Y - V domain, and then, the effective integration of multistatic echoes can be implemented. The final STHI result allows detecting the MMT reliably. Meanwhile, according to the 3-D position where the MMT is located in the X - Y - V domain, the MMT can be localized, and its velocity can be estimated simultaneously. In May 2021, we have successfully carried out the world's first BeiDou-based PMR MMT detection experiment, and the experimental results are given to prove the effectiveness of this technique.
AB - This article puts forward a BeiDou-based passive multistatic radar (PMR) maritime moving target (MMT) detection technique via space-time hybrid integration (STHI) processing. Compared with passive bistatic radar (PBR), the utilization of multiple satellites provides an improvement in MMT detection performance, together with the capabilities of localization and velocity estimation. However, the multiple satellite transmitters cause the differences principally in bistatic range and Doppler centroid (DC) of the MMT. To integrate the PMR echoes, the biggest challenge is the two differences that need to be handled. In the proposed technique, first, the centroid-compensated keystone transform (CCKT) is proposed and applied to each PBR echo. It not only corrects range cell migration (RCM) but also equalizes the DC to the same. Then, the long-time integration is performed on each PBR echo, after which it is integrated into the range-Doppler frequency rate (DFR) domain. Finally, in order to settle the difference in bistatic range, an MMT position and velocity domain (i.e., the X - Y - V domain) is constituted. The obtained multiple range-DFR maps are projected to the X - Y - V domain, and then, the effective integration of multistatic echoes can be implemented. The final STHI result allows detecting the MMT reliably. Meanwhile, according to the 3-D position where the MMT is located in the X - Y - V domain, the MMT can be localized, and its velocity can be estimated simultaneously. In May 2021, we have successfully carried out the world's first BeiDou-based PMR MMT detection experiment, and the experimental results are given to prove the effectiveness of this technique.
KW - BeiDou-based passive radar
KW - maritime moving target (MMT) detection
KW - maritime surveillance
KW - passive multistatic radar (PMR)
KW - space-time hybrid integration (STHI)
UR - https://www.scopus.com/pages/publications/85126327296
U2 - 10.1109/TGRS.2021.3128650
DO - 10.1109/TGRS.2021.3128650
M3 - 文章
AN - SCOPUS:85126327296
SN - 0196-2892
VL - 60
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
ER -