Compression of SAR Raw Data with Normalized Adaptive Predictive Vector Quantization
归一化自适应预测矢量量化算法压缩SAR原始数据

This paper presents a new SAR raw data compression algorithm named Normalized Adaptive Predictive Vector Quantization (NAPVQ). The normalized SAR raw data are firstly processed with vector linear predictor, and then the error vectors are compressed with vector quantizer. Regarded as an extension of the differential pulse code modulation in the vector quantization, the NAPVQ achieves a better performance gain than the Block Adaptive Vector Quantization (BAVQ) and the Normalized Predictive Adaptive Quantization (NPAQ). With the analyses of algorithm complexity, the proposed algorithm shows a good performance/complexity trade-off and accommodates the requirement in engineering applications.