一种SAR原始数据压缩新算法

 由于合成孔径雷达（SAR）原始数据的相关性很低，直接压缩原始数据是比较困难的。因此提出一种新算法，先对SAR原始数据做距离聚焦处理，使其在方位向具有较强的相关性，再沿方位向做线性预测，并对预测差值系列做块自适应量化。实验表明，在相同比特率条件下，该算法得到的数据域信噪比和图像域信噪比均比块自适应量化(BAQ)算法高，计算量远小于有关文献给出的距离聚焦后的压缩方法，具有一定实用价值。

A Novel Algorithm for SAR Raw Data Compression

It is difficult to directly compress synthetic aperture radar(SAR)raw data for the low relativity.In this paper,a new algorithm is put forward.Range focusing is imposed to SAR raw data,which leads to comparatively high relativity,then a linear prediction is performed along the azimuth direction,and block adaptive quantization is used to the prediction error series.The experiments manifest that with same bit rate,signal to quantization noise ration(SQNR)and signal to distor tion noise ratio(SDNR)after using the algorithm proposed in this paper surpass that of block adaptive quantization(BAQ)algorithm.The calculation in this paper is far less than that of compression method after range focusing advised in corresponding reference.The algorithm proposed in this paper has practical value in some degree.