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In terms of the global coverage provided by global navigation satellite system (GNSS) signals, radar images of a large field-of-view can be obtained via passive synthetic aperture radar (SAR) using these signals of opportunity. Usually, large field-of-view imaging is challenging using conventional SAR methods owing to the space-variant resolution. In addition, only a moderate range resolution can be provided by the GNSS transmitters in the passive SAR system. In this article, an optimal imaging method for a large field-of-view using GNSS-based passive SAR is proposed, which exploits the inherent multistatic nature of GNSS. At first, the spatial resolution of each scatterer in the observation area relative to each GNSS transmitter is calculated according to the geometry. Then, the selection of the transmitter set is modeled as an optimization problem, where the minimal resolution cell is used as the optimal criterion. After that, an evolutionary algorithm is applied to solve the optimization problem. Finally, the space-time combination of the echoes over a long dwell time concerning selected GNSS transmitters is performed to form the radar image with a minimal spatial resolution. The proposed method is extensively validated using two experimental datasets, where the passive radar consists of BeiDou satellites and a fixed receiver. The spatial resolution improvement and the large field-of-view imaging capability of the proposed method are forcefully demonstrated according to the experimental results.

Optimal GNSS-Based Passive SAR Large Field-of-View Imaging via Multistatic Configuration: Method and Experimental Validation