Bistatic Forward-Looking SAR Focusing Using $\omega\hbox{--}k$ Based on Spectrum Modeling and Optimization

Abstract

Bistatic synthetic aperture radar (SAR) is able to break through the limitation of monostatic SAR on forward-looking area imaging with appropriate geometry configurations. Thanks to such an ability, bistatic forward-looking SAR (BFSAR) has extensive potential practical applications. For the focusing problem of conventional side-looking SAR, $\omega\hbox{--}k$ algorithm is accepted as the ideal solution. In this paper, the $\omega\hbox{--}k$ algorithm will be discussed in BFSAR geometry. As for the bistatic configuration, spatial domain linearization procedure should be carried out to extract a range variable from the point target reference spectrum (PTRS) in the existing $\omega\hbox{--}k$ algorithms. With respect to the BFSAR geometry, nevertheless, the linearization procedure reduces the accuracy of PTRS seriously. To cope with such a problem, a novel $\omega\hbox{--}k$ algorithm for BFSAR is proposed. In the proposed method, the range variable is modeled as a parameterized polynomial, and the corresponding PTRS with respect to two-dimensional frequencies is established. Then, the parameters are estimated by differential evolution to minimize the PTRS errors for each range coordinate and frequency point. Based on the estimated PTRS, the BFSAR data can be focused well by the proposed $\omega\hbox{--}k$ algorithm. Simulation results verify the effectiveness of the proposed method.