BeiDou-Based Passive Multistatic Radar Maritime Moving Target Detection Technique via Space–Time Hybrid Integration Processing

Abstract

This article puts forward a BeiDou-based passive multistatic radar (PMR) maritime moving target (MMT) detection technique via space&#x2013;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 <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> domain) is constituted. The obtained multiple range-DFR maps are projected to the <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> domain, the MMT can be localized, and its velocity can be estimated simultaneously. In May 2021, we have successfully carried out the world&#x2019;s first BeiDou-based PMR MMT detection experiment, and the experimental results are given to prove the effectiveness of this technique.