栅格编码量化在合成孔径雷达数据压缩中的应用

【作者】 张毅；

【导师】 王岩飞；

【作者基本信息】 中国科学院研究生院（电子学研究所） ， 通信与信息系统， 2003， 硕士

【摘要】 数据压缩技术是合成孔径雷达(SAR)必须具备的关键技术之一。随着SAR分辨率、测绘带宽等性能指标的不断提高，SAR输出的数据率大大增加。尤其对于未来的星载SAR，将从目前仅获取雷达原始数据向同时完成星上实时成像的技术水平发展。这样，数据压缩算法就需要满足对SAR的原始数据和图像数据同时做压缩处理的需求。 论文在回顾了以往SAR使用的原始数据压缩算法后，引入了一种新的数据压缩编码算法：栅格编码量化(TCQ)。TCQ算法充分利用了卷积码的特性，采用信号空间扩展的方法来增大量化信号的欧式距离，从而达到提高量化性能的目的。 本文针对未来星载SAR星上实时成像的技术发展，提出了采用统一的TCQ算法对SAR原始数据和实时成像图像数据做压缩处理的思想，并设计了具有更多状态数的栅格用于编码试验。这一思想的理论基础在于，TCQ作为一种通用的信源编码算法，可以对各种数据源做编码处理；而以往在SAR中应用的BAQ、BFPQ等算法都是针对SAR原始数据的统计特性而设计的，具有一定的局限性。通过对SAR原始数据的压缩试验证明，TCQ算法较BAQ算法在压缩数据的信噪比上有较大的提高。同时，采用具有更多状态数的栅格设计方案，编码数据的性能指标较国外文献中的设计方案也有了进一步的提高。论文还采用TCQ算法对SAR图像进行了压缩试验，结果表明，经过TCQ算法压缩后的图像具有较高的信噪比，而且图像失真小，可以作为今后星载、机载SAR平台进行数据压缩的一种可选择的技术方案。更多还原

【Abstract】 The data compression technique is an essential one of Synthetic Aperture Radar (SAR). However, the ratio of the data is greatly dependent on the improved radar’s resolution and the increasing swath. Techniques in SAR, especially in space-borne ones, develop toward achieving both raw data acquisition, which is the current state of the art, and on-board Real-time Imaging. Therefore, data compression algorithm will be developed to realize compressing both raw data and SAR images in the future.After reviewing compression algorithms in SAR, the author introduces a new compression algorithm: Trellis Coded Quantization (TCQ). The TCQ algorithm takes advantage of convolution code, and enlarges the Euclidean distances among quantized data by expanding data dimensions.The author puts forward a method of uniform TCQ algorithm to compress SAR raw data and images. According to real-time imaging technique on space-borne SAR, and then designs a multi-state trellis with for compressing tests. The principle of the method lies in: TCQ is a general source-coding algorithm to process various data. However, the BAG, BFPQ algorithms, are developed only in SAR applications. The performance of TCQ seems to be higher SNR than BAQ in compressed data. The design scheme with a multi-state trellis states also shows a better SNR performance than current reported schemes. The author, in the meanwhile, uses TCQ to implement SAR image compressions. The result proves that the compressed images are high PSNR and low distortion characters, which is suitable to be used in space-borne and airborne SAR systems.更多还原