摘要
A signal processing method for high-speed underwater acoustic transmission of image is presented. It has two parts. Part 1 introduces signal processing for underwater acoustic coherent communication. Part 1 includes 3 technical points. （1） Doppler shift compensation. Chirp signals are inserted between data packages. A correlation process between two copy correlation functions gives more accurate estimation of the mean Doppler shift. Then it could be compensated by resampling the data. In adaptive decision feedback equalizer （DFE） an adaptive phase compensator with fast self-optimized least mean square （FOLMS） adaptation algorithm is utilized resulting in better motion tolerance than compensators with 2nd order Phase-Lock Loop algorithm. The performance of the combination of mean Doppler shift compensation and adaptive phase compensator is quite good. （2） A diversity combiner （DC） used in advance of equalizer. Both combiner and adaptive DFE are based on FOLMS adaptation algorithm. This results in reduced computation complexity and better performance. （3） Cascaded equalizer and Turbo-Trellis Coded Modulation （TCM） decoder and the iteration algorithm. A new bitsymbol converter based on Soft Output Viterbi Algorithm （SOVA） is studied. Comparing with the traditional decision, coding and mapping algorithm, the new converter can reduce Bit Error Rate（BER） by nearly 2 orders. Part 2 is mainly around a robust image compression algorithm. Based on Discrete wavelet transform and fixed length coding, a robust compression algorithm for acoustic image is studied. The algorithm includes 4 technical points. （1） Utilizes CDF9/7 wavelet bases to transform the images. （2） Analyses the energy distribution of subband coefficients. Suitable transformation layer number is 3. （3） Applies different quantization steps to different subbands in accordance with their energy distribution. （4） Uses fixed length coding to prevent error propagation. The results show the algorithm achieves a bal
A signal processing method for high-speed underwater acoustic transmission of image is presented. It has two parts. Part 1 introduces signal processing for underwater acoustic coherent communication. Part 1 includes 3 technical points. （1） Doppler shift compensation. Chirp signals are inserted between data packages. A correlation process between two copy correlation functions gives more accurate estimation of the mean Doppler shift. Then it could be compensated by resampling the data. In adaptive decision feedback equalizer （DFE） an adaptive phase compensator with fast self-optimized least mean square （FOLMS） adaptation algorithm is utilized resulting in better motion tolerance than compensators with 2nd order Phase-Lock Loop algorithm. The performance of the combination of mean Doppler shift compensation and adaptive phase compensator is quite good. （2） A diversity combiner （DC） used in advance of equalizer. Both combiner and adaptive DFE are based on FOLMS adaptation algorithm. This results in reduced computation complexity and better performance. （3） Cascaded equalizer and Turbo-Trellis Coded Modulation （TCM） decoder and the iteration algorithm. A new bitsymbol converter based on Soft Output Viterbi Algorithm （SOVA） is studied. Comparing with the traditional decision, coding and mapping algorithm, the new converter can reduce Bit Error Rate（BER） by nearly 2 orders. Part 2 is mainly around a robust image compression algorithm. Based on Discrete wavelet transform and fixed length coding, a robust compression algorithm for acoustic image is studied. The algorithm includes 4 technical points. （1） Utilizes CDF9/7 wavelet bases to transform the images. （2） Analyses the energy distribution of subband coefficients. Suitable transformation layer number is 3. （3） Applies different quantization steps to different subbands in accordance with their energy distribution. （4） Uses fixed length coding to prevent error propagation. The results show the algorithm achieves a bal
基金
supported by the National High Technology Research and Development Program of China(2002AA401004).
