一种基于动态解码的SAR原始数据饱和校正方法

A Method for Correcting Saturation Effect in SAR Raw Data Based on Dynamic Decoding

由于星载SAR原始回波数据的量化动态范围通常较小,故实际运行中,原始数据饱和的情况时有发生,成为影响图像质量的重要因素之一。该文针对星载SAR常用的均匀量化和分块自适应量化(BAQ)压缩两种方式,分别提出了基于动态解码的饱和校正方法,有效减小了图像的饱和功率损失,提高了SAR图像辐射精度,并改善了图像信噪比。仿真结果验证了该文方法的有效性。

Caused by the limited quantization dynamic range of the spaceborne SAR, the echo saturation phenomenon happens between timesduring spaceborne SAR data acquiring. In this paper, saturation correction methods based on dynamic decoding are proposed for uniform quantization and Block Adaptive Quantization （BAQ）, which are two of the most commonly used quantization method in spaceborne SAR. The dynamic decoding methods can alleviate the image power loss caused by saturation, improve the radiation precision, and enhance the image signal-to-noise ratio. The simulation results validate the effectiveness of the proposed methods.