ZHU Weiqing1 ZHU Min1 WANG Junwei1,2 HUANG Haiyun1,2
(1 Ocean Acoustic Technology Lab., Institute Of Acoustics, Chinese Academy of Sciences Beijing 100190)
(2 Graduate University of Chinese Academy of Sciences Beijing 100049)
Received Mar.25, 2008
Revised May 6, 2008
Abstract 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 sampling 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 bit-symbol 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) Used fixed length coding to present error propagation. The results show the algorithm achieves a balance among image quality, compression rate, and most important, robustness to BER. The compressed bit rate of gray scale acoustic image is 0.85 bit/pixel. Image quality remains good when BER is lower than 10-3. There are some small dirty points when BER rises to 10-2. Based on the signal processing techniques above mentioned, an underwater acoustic communication system is built. Its operational frequency band is (7.5-12.5) kHz. Its receiving array is an 8 elements uniform linear array. QPSK and 8PSK modulation and iteration algorithm for cascaded equalizer and Turbo-TCM decoder based on hard SOVA are used. The system has been tested in Qingdao Lake. Low BER is achieved in 5.5 km range when data rate is 10 kbps. One gray scale image can be transmitted in 7 s. The product of its communication distance and data rate is 55 km kbps.
PACS numbers: 43.30, 43.60 |
