A Novel Azimuth Channel Errors Estimation Algorithm Based on Characteristic Clusters Statistical Treatment

Azimuth multichannel techniques are promising in the high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) system. However, in practical engineering, errors among channels will significantly impact the reconstruction of multi-channel echo data, resulting in a smeared SAR image. To address this issue, a novel algorithm is proposed in this article, which based on the statistical treatment of characteristic clusters. In this algorithm, separately channel imaging is carried out firstly, then the image is divided into a certain number of sub-images, then the characteristic clusters and characteristic points in each sub-image are searched, and the positions, amplitude and phase information of the characteristic points are utilized to obtain the range synchronization time errors, amplitude errors and phase errors among channels. Compared with traditional methods, the proposed method do not need to be iterated, nor do they need to solve the complex problem of eigenvalue decomposition of covariance matrix. More gratifying, it can utilize the ready-made imaging tools and software in single channel SAR system. The effectiveness of the proposed method is confirmed by simulation experiments and actual data processing.