星载SAR原始数据实用化数据域压缩算法量化与饱和误差解析

doi:10.7523/j.issn.2095-6134.2011.1.014

中国科学院大学学报 ›› 2011, Vol. 28 ›› Issue (1): 94-100.DOI: 10.7523/j.issn.2095-6134.2011.1.014

星载SAR原始数据实用化数据域压缩算法量化与饱和误差解析

华斌^1,2,3, 祁海明^1,2, 李信^1,2,3, 张平¹

1. 中国科学院电子学研究所,北京 100190;
2. 微波成像技术国家重点实验室,北京 100190;
3. 中国科学院研究生院,北京 100049

收稿日期:2010-03-10 修回日期:2010-05-12 发布日期:2011-01-20
基金资助:
中国科学院优秀博士论文院长奖专项基金(0813260042)和微波成像技术国家重点实验室基金(9140C1903031003)资助 

Analysis of the quantization and saturation error for space-borne SAR raw data compression algorithm in data domain

HUA Bin^1,2,3, QI Hai-Ming^1,2, LI Xin^1,2,3, ZHANG Ping¹

1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190,China;
2. National Key Laboratory of Microwave Imaging Technology, Beijing 100190, China;
3. Graduate University, Chinese Academy of Sciences, Beijing 100049,China

Received:2010-03-10 Revised:2010-05-12 Published:2011-01-20

摘要/Abstract

摘要：

给出了实用化压缩算法(分块自适应算法及截取高位算法)数据域量化与饱和误差的解析表达式,建立了实用化压缩算法数据域信噪比与回波信号标准差之间的关系.最后,将理论推导结果与数据仿真结果、实测数据结果相比较,验证了理论推导结果的正确性,该方法为星载SAR原始数据压缩比选取提供了理论指导.

关键词: 合成孔径雷达, 原始数据压缩, 分块自适应量化, 量化误差, 饱和误差

Abstract:

In this paper, the analytical formula of the quantization and saturation error induced by block adaptive quantization (BAQ) and Interception of High (IH) compression algorithms are derived. Moreover, the relationship between the standard deviation of input echo signal (SDIS) and the Signal-to-noise ratio (SNR) of these two compression algorithms is given. Finally, our method is verified by using simulated SAR raw data and real data, and is shown to be a good criterion for choosing SAR raw data compression ratio.

Key words: synthetic aperture radar (SAR), raw data compression, block adaptive quantization (BAQ), quantization error, saturation error

中图分类号:

TN957.52

华斌, 祁海明, 李信, 张平. 星载SAR原始数据实用化数据域压缩算法量化与饱和误差解析[J]. 中国科学院大学学报, 2011, 28(1): 94-100.

HUA Bin, QI Hai-Ming, LI Xin, ZHANG Ping. Analysis of the quantization and saturation error for space-borne SAR raw data compression algorithm in data domain[J]. , 2011, 28(1): 94-100.

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星载SAR原始数据实用化数据域压缩算法量化与饱和误差解析

Analysis of the quantization and saturation error for space-borne SAR raw data compression algorithm in data domain

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