水声高速图像传输信号处理方法

研究了水声图像高速传输信号处理方法,它包括两个方面,一方面是水声相干通信信号处理方法,其中:(1)多普勒频移补偿,在数据包的前后两端插入已知线性调频(Chirp)信号,拷贝相关后求互相关,估计相对多普勒平均频移。在自适应判决反馈均衡器中加上自适应相位补偿器,采用快速自优化最小均方(LMS)算法,与其对应的速度容限优于常用的二阶锁相环相位补偿器的。两种补偿方法联合工作时,性能优良。(2)带有分集合并器的自适应判决反馈均衡器的算法是快速自优化的LMS算法,计算量小,性能优良。(3)自适应判决反馈均衡器与Turbo-网格编码调制(TCM)译码器级连、迭代算法。研究了基于软输出维特比(SOVA)方法的新型的比特-符号转换器,用它时误比特率(BER)比常规编码、映射方法的近似小2个数量级。另一方面是抗误码的图像压缩方法。本文基于数字小波变换和定长编码方法,研究了声图像的压缩。它包括:(1)选用CDF9/7小波进行小波变换。(2)对小波系数子带能量进行统计分析,三层小波分解是合适的。(3)对不同能量的子带采用不同的量化步长。(4)采用定长编码算法。结果表明声图像压缩比特率为0.85。当BER小于10^-3时,图像质量完好。当BER小于10^-2时,图像中出现少量小黑白点。在上述基础上研制了水声通信机,频带为(7.5~12.5) kHz,接收声呐阵为8基元等距线阵,信号为QPSK和8PSK。在中国千岛湖进行了湖试,采用SOVA硬迭代算法,达到了低BER。传输一幅256×256×8的声图需时约7s。传输距离与传输速率之积为55 km kbps。

Signal processing for high speed underwater acoustic transmission of image

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 functions gives more accurate estimation of the mean Doppler shift. Resample the data to compensate it. 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 2^nd 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) is used in advance of equalizer. Both combiner DC and adaptive DFE are based on FOLMS adaptation algorithm and have reduced computation complexity and good 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, new converter can reduce Bit Error Rate (BER) by nearly 2 orders. Part 2 is a robust image compression algorithm. Based on digital 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 to transform the images. (2) Analyses the energy distribution of the subband coefficients. A 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 balance among image quality, compression rate, and most important, robustness to BER. The bit rate of compressed gray scale acoustic image are 0.85 bit/pixel. 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 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 is tested in Qian Dao 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 second. The product of its communication distance and data rate is 55 km kbps.