载人潜水器“蛟龙”号的水声通信信号处理

蛟龙号的水声通信机实现了世界上首次7000 m深度的潜器与母船间的图像、语音、数据和文字的水声通信传输。研究了适用于载人潜水器的水声通信信号处理。(1)它有4种通信功能:1)相干水声通信,传输速率为5~15 kbps,用于传输图像;2)非相干水声通信,传输速率300 bps,传输文字、指令和数据;3)扩频水声通信,传输速率16 bps,传输指令;4)水声语音通信,采用单边带调制技术传输语音。(2)相干水声通信信号处理方法主要是自适应多普勒补偿的多通道自优化判决反馈自适应均衡器,它与Turbo码级联工作,同时采用定长编码的小波图像压缩方法。(3)声呐线阵吊放至水中一定深度,实现空间分集合并技术。(4)太平洋水域试验表明,水声通信机的作用距离几乎覆盖了所有地球海洋的深度,7s或14s传输一幅光图或声图。      

一种水声信道均衡器的混合算法

水声高速相干通信中使用自适应均衡对抗信道在接收信号中产生的码间串扰。目前,1/2分数间隔采样的判决反馈均衡器结构得到了广泛的应用。本文分析了几种自适应算法在此种均衡器结构下的性能,结合浅海水声信道的特点,提出了一种快速卡尔曼滤波和快速自优化最小均方的混合算法,模拟及海试结果表明,该混合算法在计算复杂度、收敛速度以及稳定性方面都有很好的性能,已经应用到了水声实时高速通信系统当中。     

Adaptive and efficient nonlinear channel equalization for underwater acoustic communication

We investigate underwater acoustic (UWA) channel equalization and introduce hierarchical and adaptive nonlinear (piecewise linear) channel equalization algorithms that are highly efficient and provide significantly improved bit error rate (BER) performance. Due to the high complexity of conventional nonlinear equalizers and poor performance of linear ones, to equalize highly difficult underwater acoustic channels, we employ piecewise linear equalizers. However, in order to achieve the performance of the best piecewise linear model, we use a tree structure to hierarchically partition the space of the received signal. Furthermore, the equalization algorithm should be completely adaptive, since due to the highly non-stationary nature of the underwater medium, the optimal mean squared error (MSE) equalizer as well as the best piecewise linear equalizer changes in time. To this end, we introduce an adaptive piecewise linear equalization algorithm that not only adapts the linear equalizer at each region but also learns the complete hierarchical structure with a computational complexity only polynomial in the number of nodes of the tree. Furthermore, our algorithm is constructed to directly minimize the final squared error without introducing any ad-hoc parameters. We demonstrate the performance of our algorithms through highly realistic experiments performed on practical field data as well as accurately simulated underwater acoustic channels.     

Efficient processing of acoustic signals for high-rate information transmission over sparse underwater channels

For underwater acoustic channels where multipath spread is measured in tens of symbol intervals at high transmission rates, multichannel equalization required for bandwidth-efficient communications may become prohibitively complex for real-time implementation. To reduce computational complexity of signal processing and improve performance of data detection, receiver structures that are matched to the physical channel characteristics are investigated. A decision-feedback equalizer is designed which relies on an adaptive channel estimator to compute its parameters. The channel estimate is reduced in size by selecting only the significant components, whose delay span is often much shorter than the multipath spread of the channel. Optimal coefficient selection (sparsing) is performed by truncation in magnitude. This estimate is used to cancel the post-cursor ISI prior to linear equalization. Spatial diversity gain is achieved by a reduced-complexity pre-combining method which eliminates the need for a separate channel estimator/equalizer for each array element. The advantages of this approach are reduction in the number of receiver parameters, optimal implementation of sparse feedback, and efficient parallel implementation of adaptive algorithms for the pre-combiner, the fractionally-spaced channel estimators and the short feedforward equalizer filters. Receiver algorithm is applied to real data transmitted at 10 kbps over 3 km in shallow water, showing excellent results.     

水声通信中基于信道辨识的盲turbo均衡方法

水声信道多途效应明显,造成接收信号存在严重的码间干扰(ISI,Intersymbol interference)。基于最小均方误差(MMSE,Minimum mean square error)准则的turbo均衡器级联了均衡和信道译码,能够有效去除ISI,并获得优良的性能。由于水声信道的时变性,传统MMSE-turbo均衡需要周期性的训练序列,以实现连续可靠的通信。训练序列虽然提高了通信的可靠性,但降低了信息的有效传输速率。因此,为提高通信效率,本文提出了一种盲turbo均衡方法,该方法通过引入新的盲信道辨识器来同时获得信道估计响应和已去除部分ISI的初步均衡输出信号,并为turbo均衡提供初始的响应参数和比特软信息。与水声通信中应用较多的盲判决反馈均衡器(DFE,Decision feedback equalizer)相比,海上实验结果证明本文提出的盲turbo均衡方法抗信道多途衰落的能力较强,并且与传统MMSE-turbo均衡相比无需训练序列,因此提高了信息的有效传输速率。     

一种正交频分复用系统抗水下时变多径信道的频率偏移估计方法

提出了一种水下正交频分复用(OFDM)系统鲁棒的频率偏移估计方法,即通信帧由一个训练帧和多个数据帧组成。其中克服大的多普勒频移,也就是粗频移估计(Rough Frequency Offset Estimation,RFOE),是通过训练帧来实现的,而克服时变的和小的多普勒频移,也就是精细多普勒频移估计(Accurate Frequency Offset Estimation,AFOE),是通过每一个数据帧实现的。RFOE和AFOE都是使用OFDM数据或循环前缀(Cyclic Prefix,CP)中没有被多径干扰的那部分数据计算得到的。在海试中,采用这种算法实现了通信速率与作用距离的乘积为133km·kbps的无误码通信,并比较了不同算法的试验结果,试验结果表明该算法能克服水下信道多径和时变的影响。      

Performance of run-length limited (4, 18) code for optical storage systems

In this paper, the authors investigate the performance of recently presented run-length limited (4, 18) code for high density optical storage systems. The construction of the code is described simply. The code has code rate R = 1/3 and density ratio (DR) = 1.67. The bit error rate (BER) performance for decision feedback equalizer (DFE) and partial response maximum likelihood (PRML) detector are simulated, considering signal-to-noise ratio (SNR) and optical channel jitter. The result shows that the performance of the code is acceptable. The encoder and decoder of the code are implemented by complex programmable logic device (CPLD) chip and the hardware resources required for encoder and decoder arelow.     

近程高速水声毫米波通信仿真与试验验证*

水声信道的严重双扩特性极大地限制了水声高速通信的稳健性。针对近程高速水声通信技术的需求,该文基于水声毫米波频段,提出了一种基于超奈奎斯特发射技术及高阶调制技术的单载波的水声毫米波通信技术。而超奈奎斯特发射技术以及高阶调制给接收机带来了极大的挑战:一是超奈奎斯特发射技术引入了严重的符号间干扰,二是高阶调制系统的符号检测对信道估计的精度要求很高。针对以上问题,该文提出了一种基于迭代信道估计技术的迭代软反馈DFE接收机技术。仿真实验表明:采用128QAM高阶调制时,在较为严重的多途衰落信道条件下,采用所提出的接收机可以在15 dB时实现无误码传输。信道水池试验证明:当通信带宽为300 kHz,通信符号率为300k符号/秒且采用64QAM调制时,在发射平台慢速运动的条件下可以实现900 kbps的净数据率,其相应的频谱利用率高达6 Bits/s/Hz。     

基于扩频码的单载波迭代频域均衡水声通信

单载波时域均衡在长时延扩展水声信道中计算量大,并对接收机参数的选择较为敏感,可靠性低,而正交频分复用信号峰均功率比高、对频率偏移敏感. 针对这些问题,提出基于扩频码的单载波块传输高速率水声通信方法和基于T/4分数间隔迭代频域均衡的接收机算法. 该接收机利用已知扩频码进行信道估计以及对由多普勒偏移引起的旋转相位进行估计,并通过一种低复杂度迭代频域均衡算法改善系统性能. 开展了湖上实验研究,结果表明在浅水1.8 km距离且复杂多径干扰条件下,利用BPSK/QPSK调制可实现10^-2–10^-4的误码率并达到1500–3000 bit/s的有效数据率. 关键词： 水声通信 单载波 频域均衡 迭代处理     

An efficient adaptive arithmetic coding image compression technology

This paper proposes an efficient lossless image compression scheme for still images based on an adaptive arithmetic coding compression algorithm. The algorithm increases the image coding compression rate and ensures the quality of the decoded image combined with the adaptive probability model and predictive coding. The use of adaptive models for each encoded image block dynamically estimates the probability of the relevant image block. The decoded image block can accurately recover the encoded image according to the code book information. We adopt an adaptive arithmetic coding algorithm for image compression that greatly improves the image compression rate. The results show that it is an effective compression technology.     

相干水声通信幅相加权空间分集均衡算法

水声信道的典型特点为多普勒频移严重、可利用带宽窄以及强多径干扰。空间分集均衡技术是相干水声通信中克服信道多径干扰,消除码间干扰的一种有效手段。为了极大化地输出阵增益,结合无源相位共轭方法和多通道均衡算法,本文设计了组合信噪干比的全新信道评价方法。利用改进的Sigmoid函数对各通道接收信号的幅度进行加权处理;采用二阶锁相环跟踪各通道信号的相位变化,实现各通道信号同相累加。将各通道低通滤波后的信号能量归一化,采用了分数阶-判决反馈分集均衡器,加入各通道权重系数实现了水声通信系统的分集均衡接收。仿真结果和湖试数据处理结果均表明,优化的幅相加权分集均衡接收算法能抵消多径和噪声的干扰,性能优于等增益合并接收算法。湖试数据处理结果误码率降低了1.8%。      

一种鲁棒性强的OFDM 水声通信系统*

为了在不同衰落水声信道下实现正交频分复用水声通信,该文提出了一种鲁棒性强的正交频分复用水声通信方案,方案包括编码调制、信道估计和多普勒估计等内容。为了使该系统更稳健,整个信道编码分为两个步骤。首先,循环冗余校验编码器和里德-所罗门编码器用于编码整个数据包,然后循环冗余校验编码器和Turbo 编码器用于编码每个数据帧,其中比特交织编码调制技术用来对抗信道的时变特性。为了得到水声信道估计,使用线性最小均方误差估计器来处理导频数据得到信道估计值。多普勒估计包括帧的多普勒估计和符号的多普勒估计。实验结果表明该系统在不同的衰落信道下都能实现正确的跟踪和译码,系统的鲁棒性能优越。此外,该系统算法计算简单,易于实现,具有良好的工程应用价值。     

Spatial diversity and combination technology using amplitude and phase weighting method for phase-coherent underwater acoustic communications

The UWA channel is characterized as a time-dispersive rapidly fading channel,which in addition exhibits Doppler instabilities and limited bandwidth. To eliminate intersymbol interference caused by multipath propagation, spatial diversity equalization is the main technical means. The paper combines the passive phase conjugation and spatial processing to maximize the output array gain. It uses signal-to-noise-plus-interference to evaluate the quality of signals received at different channels. The amplitude of signal is weighted using Sigmoid function. Second order PLL can trace the phase variation caused by channel, so the signal can be accumulated in the same phase. The signals received at different channels need to be normalized. It adopts fractional-decision feedback diversity equalizer(FDFDE) and achieves diversity equalization by using different channel weighted coefficients. The simulation and lake trial data processing results show that, the optimized diversity receiving equalization algorithm can improve communication system's ability in tracking the change of underwater acoustic channel,offset the impact of multipath and noise and improve the performance of communication system.The performance of the communication receiving system is better than that of the equal gain combination. At the same time, the bit error rate(BER) reduces 1.8%.     

An image joint compression-encryption algorithm based on adaptive arithmetic coding

Through a series of studies on arithmetic coding and arithmetic encryption, a novel image joint compression- encryption algorithm based on adaptive arithmetic coding is proposed. The contexts produced in the process of image compression are modified by keys in order to achieve image joint compression encryption. Combined with the bit-plane coding technique, the discrete wavelet transform coefficients in different resolutions can be encrypted respectively with different keys, so that the resolution selective encryption is realized to meet different application needs. Zero-tree coding is improved, and adaptive arithmetic coding is introduced. Then, the proposed joint compression-encryption algorithm is simulated. The simulation results show that as long as the parameters are selected appropriately, the compression efficiency of proposed image joint compression-encryption algorithm is basically identical to that of the original image compression algorithm, and the security of the proposed algorithm is better than the joint encryption algorithm based on interval splitting.     

An adaptive channel equalizer using self-adaptation bacterial foraging optimization

In this paper we propose a self-adaptation bacterial foraging optimization (SA-BFO) approach for an adaptive channel equalizer in which the weights of the equalizer are optimized to minimize the mean square error (MSE) and bit error rate (BER). The adaptive channel equalizer at the receiver removes or reduces the effects of inter symbol interference (ISI) and noise. Tests demonstrate that the proposed adaptive channel equalizer provides better convergence speed and minimal MSE and BER compared to a BFO and a normalized least mean square (NLMS) based equalizer.     

变步长似p范数约束稀疏水声信道估计方法

针对范数约束类归一化最小均方(NLMS)算法在正交频分复用(OFDM)稀疏水声信道估计中误码率较高的问题,提出一种改进的变步长似p范数约束信道估计方法。采用改进双Logistic函数构造步长,并将误差信号自相关函数引入其中,实时调整步长和零吸引项,使得收敛速度和估计精度能够很好地折中。算法仿真结果表明,在浅海多径稀疏水声信道下,相比于传统方法,所提出的信道估计获得的最高性能提升为收敛速度提高72.3%,稳态误差降低95.9%。湖上试验数据处理结果显示,相比于传统信道估计方法,所提出的方法能使通信误码率降低2~3个数量级,实现零误码水声通信。      

基于率失真斜率提升的干涉多光谱图像压缩

提出了一种基于优化截取内嵌块编码的矩形感兴趣区域编码的干涉多光谱卫星图像压缩方法,不需要对小波域的系数进行提升,而是在码流组织时通过对多光谱区域自适应失真跟踪实现。解码器不需要进行小波域系数的逆提升,即可达到感兴趣区域的恢复质量要求。改变感兴趣区域的失真指标,只需要再次进行码流组织,而不需要重复进行优化截取内嵌块编码的T1编码,因此更为有效、灵活。同时提出了一种整型率失真斜率估计值快速算法,既可以保证率失真优化截取的精度,又避免了率失真斜率的浮点除法计算和浮点表示,降低了系统的复杂度。该算法适合干涉多光谱卫星图像压缩。     

水声通信中后验符号概率密度分布及概率成形容量分析

考虑到实际水声信道复杂特性对水声通信的影响,对系统的通信容量进行计算分析,并研究了一种适用于水声信道的容量评估算法。文中通过对不同条件下的均衡器输出的后验符号特性进行统计分析,提出了一种基于后验高斯分布的符号方差分段转移函数模型。在此基础上,采用Maxwell-Boltzmann分布来改变均衡器输出符号的成形分布,即引入概率成形技术对实际的水声通信系统容量进行评估分析。最后通过对水池和湖试多径信道数据的处理,获得了不同调制方式下的通信容量。结果显示,在特定的信噪比区间内,概率成形技术比传统的等概率映射的容量提升最大可达0.5 bits/symbol。      

点对点移动水声通信技术研究

点对点移动水声通信是实现由活动和静止节点共同构成的水声数据通信网的关键技术之一. 对移动水声通信声信道特性进行了分析,指出不同途径到达的声线对应的多普勒频偏不一致,进一步加大了多途扩展产生的码间干扰的复杂性,不利于水声通信. 提出单阵元被动式相位共轭镜信道均衡技术,可实时自动补偿多普勒频偏,并聚焦多途信号. 将单阵元被动式相位共轭应用于Pattern时延差编码移动水声通信系统,进行了移动水声通信试验,湖试结果验证了其消除码间干扰性能及本文水声通信系统的鲁棒性. 关键词： 移动水声通信 被动式相位共轭镜 时变信道 码间干扰     

Performance analysis of adaptive equalization for coherent acoustic communications in the time-varying ocean environment

Equations are derived for analyzing the performance of channel estimate based equalizers. The performance is characterized in terms of the mean squared soft decision error (sigma2(s)) of each equalizer. This error is decomposed into two components. These are the minimum achievable error (sigma2(0)) and the excess error (sigma2(e)). The former is the soft decision error that would be realized by the equalizer if the filter coefficient calculation were based upon perfect knowledge of the channel impulse response and statistics of the interfering noise field. The latter is the additional soft decision error that is realized due to errors in the estimates of these channel parameters. These expressions accurately predict the equalizer errors observed in the processing of experimental data by a channel estimate based decision feedback equalizer (DFE) and a passive time-reversal equalizer. Further expressions are presented that allow equalizer performance to be predicted given the scattering function of the acoustic channel. The analysis using these expressions yields insights into the features of surface scattering that most significantly impact equalizer performance in shallow water environments and motivates the implementation of a DFE that is robust with respect to channel estimation errors.