An Omega-K algorithm for bistatic forward-looking SAR based on spectrum modeling and optimization

Abstract

With appropriate geometry configurations, bistatic Synthetic Aperture Radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. For the focusing problem of BFSAR, Omega-K algorithm is of great significance. As for the bistatic configuration, spatial domain linearization procedure should be carried out in the existing Omega-K algorithms to simplify the point target reference spectrum (PTRS). As for the BFSAR geometry, nevertheless, the linearization procedure reduces the accuracy of PTRS seriously. To cope with such a problem, an Omega-K algorithm based on differential evolution is proposed. Firstly, a parameterized model with respect to range and 2-dimensional frequencies of the PTRS 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. Simulation results verify the effectiveness of the proposed method.