LAUSR

Multi-channel synthetic aperture radar (SAR) in azimuth can overcome the minimum-antenna-area constraint of the conventional SAR in high-resolution and wide-swath (HRWS) imaging. However, the SAR system suffers from amplitude and phase mismatch among channels and nonideal antenna pattern, which will result in azimuth ambiguity and ghost targets in the final image. Therefore, taking the nonbandlimited signal and channel errors into account, a practical azimuth ambiguity-to-signal ratio (AASR) model of multi-channel SAR system is established. Meanwhile, the baseband Doppler centroid (DC) frequency related to channel errors also has an influence on image quality. Then, an effective method is proposed to calculate the baseband DC frequency according to the jumping points of the channel phase errors estimate. Subsequently, considering the effect of azimuth antenna pattern (AAP), a corresponding relationship between the ideal steering vectors and the signal subspace from the decomposing covariance matrix is established. After that, based on the uniqueness of the signal subspace and the correct corresponding relationship, an accurate method is proposed to estimate the channel phase errors by minimizing the minimum mean square error (MMSE) of the signal subspace. Finally, an accurate multi-channel SAR imaging diagram is shown to effectively mitigate the azimuth ambiguous energy caused by channel errors. Simulation and real data experiments, including four channel airborne SAR data with a bandwidth of 210 MHz and the Chinese Gaofen-3 dual receiving channel (DRC) spaceborne SAR data, validate the effectiveness of the proposed calibration method, particularly in low signal-to-noise ratio (SNR).