NDLI: A study of spaceborne SAR raw data compression error based on a statistical model of quantization interval transfer probability

Content Provider	Springer Nature Link
Author	Li, Xin Qi, HaiMing Hua, Bin Lei, Hong Yu, WeiDong
Copyright Year	2010
Abstract	SAR raw data signal to noise ratio (SNR) after compression is of great importance since the choice of compression ratio is dependent on it during SAR system design and application analysis. The signal to quantization noise ratio (SQNR) generally used may not precisely indicate the relationship between signal and noise. Considering the thermal noise, a statistical model of quantization interval transfer probability is proposed in this paper. SNR mapping between SAR raw data before analog to digital converter (ADC) and after block adaptive quantization (BAQ) over the whole set of saturation degree is obtained using this model. When the power of echo is small with low SNR, after 1, 2, 3 or 4 bits BAQ compression, SNR has tiny difference among the four compression levels. When the power of the echo is medium with higher SNR, the SNR degradation after BAQ is about 5 dB with each bit decreasing from 4 bits. If voltage of the echo is higher than the clipping point of ADC, SNR after ADC and BAQ degrades stepwise. The higher the saturation degree of SAR raw data, the worse the SNR is. Simulated Gaussian data and real SAR raw data are used to verify the theoretical results, which are useful in the choice of BAQ compression ratio and further application analysis.
Starting Page	2352
Ending Page	2362
Page Count	11
File Format	PDF
ISSN	1674733X
Journal	Science in China Series : Information Sciences
Volume Number	53
Issue Number	11
e-ISSN	18691919
Language	English
Publisher	SP Science China Press
Publisher Date	2010-10-22
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	SAR raw data compression SNR saturation Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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