基于FFT BAQ的SAR原始数据压缩新算法

针对合成孔径雷达(synthetic aperture radar, SAR)原始数据频域压缩运算中基于快速傅里叶变换的分块自适应量化(fast Fourier transform based block adaptive quantization, FFT BAQ)算法实现复杂的问题，分析了SAR原始数据二维傅里叶变换后数据的能量分布情况。从香农率失真理论出发，利用信源微分熵确定最优的量化比特分配，提出了一种改进的FFT BAQ算法。分析了改进算法的复杂度，并与传统的FFT BAQ算法和BAQ算法做了相应的比较实验。实验表明,改进算法在保证原压缩性能的基础上降低了FFT BAQ算法的复杂度和对硬件的要求。

Improved FFT-based algorithm for SAR raw data compression

In order to solve the difficult implementation of the synthetic aperture radar (SAR) raw data compression algorithm based on fast Fourier transform-based block adaptive quantization(FFT-BAQ), the ener-gy distributing of SAR raw data after two dimensions frequency transform is analyzed, and optimum bits alloca-tion scheme is designed based on Shannon rate-distortion theory and information resource differential entropy. An improved FFT-based algorithm for SAR raw data compression is proposed. The complex level of this improved algorithm is analyzed, and the analyzed result indicates that the improved algorithm decreases the complex level and hardware requirements and keeps the excellent performance compared with the original FFT-BAQ.