Abstract
ABSTRACTUsing global navigation satellites to construct bi-static synthetic aperture radar for imaging has been a major research hotspot in passive radar. However, the low range resolution of Global Navigation Satellite signal (GNSS) limits the quality of actual scene imaging. To increase the range resolution of the imaging, a super-resolution imaging method by mixing the back-projection (BP) algorithm with truncated singular value decomposition (TSVD) is proposed. This paper first introduces the BeiDou Navigation Satellite System (BDS) signal model for ground imaging, carries out the range compression and describes the BP algorithm. Subsequently, the super-resolution method is given and some simulation results are demonstrated. Two field experimental cases, including targets of trees and ferries, are then carried out. The experimental results demonstrate the effectiveness of the proposed method.
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