Signal Processing for High Speed Underwater Acoustic Transmission of Image (March 2007)

Abstract

In this paper, a signal processing method for high-speed underwater acoustic transmission of image is presented. It has two parts. Part 1 is underwater acoustic coherent communication signal processing. Part 1 includes 3 technical points. 1. Doppler shift compensation. Chirp signals are inserted between data packages. A correlation process between two copy correlation results gives more accurate estimation of the mean Doppler shift. Resample the data to compensate it. In feedback adaptive equalizer 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 PLL algorithm. The performance of the combination of mean Doppler shift compensation and adaptive phase compensator is quite good. 2. A combiner is used in advance of equalizer. Both combiner and feedback adaptive equalizer are based on FOLMS adaptation algorithm and have reduced computation complexity and good performance. 3. Cascaded equalizer and Turbo-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, new converter can reduce BER by nearly 2 orders. Part 2 is a robust image compression algorithm. In high-speed underwater acoustic image transmission, there are always some error bits. Ordinary image compression algorithms, for example, JPEG and JPEG2000, are sensitive to error bits. One error bit may destroy whole image. So they are not suitable for high-speed underwater acoustic image transmission. Based on digital wavelet transform and fixed length coding, a robust compression algorithm for optical and acoustic image is studied. The algorithm includes 4 technical points. 1. Utilizes CDF9/7 wavelet base to transform the images. 2. Analysis the energy distribution of the subbands coefficients. A suitable transformation layer number is 3. 3. Apply different quantization steps to different subbands in accordance with their energy distribution. 4. Fixed length coding to prevent error propagation. The results show the algorithm achieves a balance among image quality, compression rate, and most important, robustness to bit error. The data rate of compressed true color optical image and gray scale acoustic image are 0.80 bit/pixel and 0.85 bit/pixel respectively. Image quality remains good when BER is lower than 10-3. There are some small dirty points when BER rise to 10-2. Based on the signal processing techniques described above, an underwater acoustic communication system is built. Its band is (7.5~12.5) kHz. Its receiving array is an equal spaced 8 elements linear array. Each element is semi-spherical directivity. QPSK and 8PSK modulation and iteration algorithm for cascaded equalizer and Turbo-TCM decoder based on Soft Output Viterbi Algorithm are used. The system is tested in Qiandao Lake, a 20-50 meters deep reservoir with lots of submerged hills. Low BER is achieved in 5.5 km rang when data rate is 10 kbps. One 256times256 true color image or gray scale image can be transmitted in 7 second. The product of its communication distance and data rate is 55 km*kbps. Without the limitation of the lake area, the product is estimated to reach 80~100 km*kbps.