Zhang Wen-chao, Wang Yan-fei, Pan Zhi-gang. Study on Amplitude-Phase Bit Allocation of AP Algorithm for SAR Raw Data Compression[J]. Journal of Electronics & Information Technology, 2008, 30(4): 1007-1010. doi: 10.3724/SP.J.1146.2006.01656
Citation:
Zhang Wen-chao, Wang Yan-fei, Pan Zhi-gang. Study on Amplitude-Phase Bit Allocation of AP Algorithm for SAR Raw Data Compression[J]. Journal of Electronics & Information Technology, 2008, 30(4): 1007-1010. doi: 10.3724/SP.J.1146.2006.01656
Zhang Wen-chao, Wang Yan-fei, Pan Zhi-gang. Study on Amplitude-Phase Bit Allocation of AP Algorithm for SAR Raw Data Compression[J]. Journal of Electronics & Information Technology, 2008, 30(4): 1007-1010. doi: 10.3724/SP.J.1146.2006.01656
Citation:
Zhang Wen-chao, Wang Yan-fei, Pan Zhi-gang. Study on Amplitude-Phase Bit Allocation of AP Algorithm for SAR Raw Data Compression[J]. Journal of Electronics & Information Technology, 2008, 30(4): 1007-1010. doi: 10.3724/SP.J.1146.2006.01656
In this paper, AP (Amplitude-Phase) algorithm for SAR raw data compression is studied and the formula of bit allocation between amplitude data and phase data is deduced based on the lower bound of rate-distortion inequality of non-normal information resource and the Lagrange multiplier, which points out that the bit allocation is decided by their differential entropy correspondingly. The uniform distribution of phase data and the Rayleigh distribution of amplitude data are investigated and the bit allocation formula is deduced according to the differential entropy of continuous information resource, which points out that the mean of amplitude is the only factor. According to the relationship between the histogram and the probability density function, a general differential entropy calculation formula is given. The two methods have their advantages and both can implement the auto-bit allocation. The validity of this method is proved by the real raw data compression experiments.
Kwok R and Johnson W T K. Block adaptive quantization ofMagellan SAR data[J].IEEE Trans. on Geosci. and RemoteSensing.1989, 27(4):375-383[2]Huneycutt B L. Spaceborne imaging Radar-C instrument[J].IEEE Trans. on Geosci. and Remote Sensing.1989, 27(2):164-169[3]Moureaux J M, et al.. Raw SAR data compression usingvector quantization[J].Int. J. Remote Sensing.1995, 16(16):3179-3187[4]Moreira A and Blaser F. Fusion of block adaptive and vectorquantizer for efficient SAR data compression[C]. Proceedingsof the International Geoscience Remote Sensing Symposium,Tokyo, 1993: 1583-1585.[5]Benz U, Strodl K, and Moreira A. A comparison of severalalgorithms for SAR raw data compression[J].IEEE Trans. onGeosci. and Remote Sensing.1995, 33(5):1266-1276[6]姚世超，王岩飞，张冰尘，廖蜀燕. 合成孔径雷达原始数据幅相压缩算法[J].电子与信息学报.2002, 24(11):1627-1633浏览[7]Pearlman W A and Senge G H. Optimal quantization of theRayleigh probability distribution[J].IEEE Trans. onComunications.1979, 27(1):101-112[8]Verdugo Lazo A C G and Rathie P N. On the entropy ofcontinuous probability distribution[J].IEEE Trans. onInformation Theory.1978, 24(1):120-122
DownLoad: