Calibrating for the satellite attitude jitter in multistatic SAR using a subspace method

With respect to a spaceborne multistatic synthetic aperture radar (SAR) system, satellite attitude jitter, consisting of yaw-, pitch-, and roll-angle components, undermines the coherent cooperation among the satellites and results in degraded imaging performance. In order to calibrate the system to compensate for the jitter, a parametric method is proposed in this study. The approach starts by deriving the echo signal with unknown jitter received by each satellite as a bistatic extended space–time model. Then, the high-order instantaneous moment of the model is obtained, which is in the form of a high-order polynomial phase array signal. Finally, the unknown jitter is estimated using the multiple signal classification method, which is a subspace method. The proposed method can improve the imaging performance by correctly calibrating the system to compensate for the jitter. Furthermore, the authors demonstrate that the proposed method outperforms conventional autofocus algorithms using the simulated raw data of a Cartwheel constellation, which is a typical flying formation of a multistatic SAR system.