LAUSR

Azimuth multichannel synthetic aperture radar (SAR) is a useful approach to solving minimum antenna area constraint and realizing high resolution and wide swath (HRWS) imaging by multichannel signal reconstruction. However, channel phase error will significantly degrade the reconstruction performance and leads to azimuth ghost. This article presents an efficient minimum entropy channel error estimation method based on fine-focused SAR image. The multichannel SAR images are obtained by using Range-Doppler imaging algorithm applied for preprocessed data of each channel. Then, the reconstruction and the residual range cell migration and residual second range compression compensation are performed to achieve multichannel fine-focused SAR images. After overlapping these multichannel fine-focused SAR images and iteratively calibrating the channel phase error, fine-focused HRWS SAR image can be achieved. Therefore, the SAR image used in the channel error estimation process can directly obtain the fine focused HRWS SAR image after minimum entropy iteration without additional imaging operations. Compared with the minimum entropy method by using the coarse-focused SAR image based on azimuth deramp, redundant reconstruction, and imaging operations are avoided. Thus, error estimation and imaging processing procedures are optimized. Processing efficiency improvement are analyzed, and simulation and acquired data processing verify the effectiveness of the proposed method.