格林函数解卷积处理的阵不变量浅海无源定位

水下声源无源定位是声呐技术重要的研究方向.针对水下声源无源定位问题,本文提出了一种基于格林函数解卷积处理的阵不变量无源定位方法.该方法使用盲解卷积算法从水平阵接收信号中提取时域格林函数,然后采用空域解卷积方法处理得到的时域格林函数,获得波束时间偏移,从波束时间偏移中计算得到阵不变量,解算目标距离,从而实现声源定位.区别...     

水下目标回波盲分离性能的瞬时频率特征评价方法

在水下主动声呐目标回波与混响盲分离中,针对分离结果顺序不确定性以及缺乏分离有效性衡量手段的问题,提出了以信号瞬时频率特征为指标的盲分离性能评价方法。推导了目标回波与混响的时频分布特性,理论表明目标回波在瞬时频率序列的中心偏离程度以及整体随机程度上低于混响,据此提取信号的瞬时频率方差与瞬时频率熵两种信号特征,并将二者作为从盲分离结果中识别目标回波的依据。海试数据结果表明,在盲分离得到的所有分离信号中,目标回波具有最小的瞬时频率特征值,并且该特征值越小,目标回波与混响的盲分离程度就越高。     

水下目标回波盲分离性能的瞬时频率特征评价方法

在水下主动声呐目标回波与混响盲分离中,针对分离结果顺序不确定性以及缺乏分离有效性衡量手段的问题,提出了以信号瞬时频率特征为指标的盲分离性能评价方法。推导了目标回波与混响的时频分布特性,理论表明目标回波在瞬时频率序列的中心偏离程度以及整体随机程度上低于混响,据此提取信号的瞬时频率方差与瞬时频率熵两种信号特征,并将二者作为从盲分离结果中识别目标回波的依据。海试数据结果表明,在盲分离得到的所有分离信号中,目标回波具有最小的瞬时频率特征值,并且该特征值越小,目标回波与混响的盲分离程度就越高。      

基于双向反射函数的水下激光引信回波仿真方法

针对鱼雷激光近炸引信探测水下近场目标的需求,开展了水下激光引信回波蒙特卡洛仿真方法研究.结合水下激光引信探测特点建立水下目标回波的蒙特卡洛仿真模型.为了提高水中非朗伯目标表面回波仿真的准确度,推导了基于双向反射函数的光子反射方向概率分布,根据概率分布随机抽样光子反射方向.仿真了不同距离和入射角度条件下的水中目标回波信号.仿真结果表明:目标回波幅度随目标距离和入射角度的增大迅速下降,目标距离在6~12m内变化时,信号峰值动态范围为11.5dB;目标距离为8m,激光入射角在0~45°内变化时,信号峰值动态范围为9.2dB.为验证仿真方法的正确性,在水池中进行水中目标蓝绿激光探测实验,实验结果和仿真结果一致.研究成果可为解决传统蒙特卡洛方法在水中非朗伯面目标回波仿真中的适用性问题及水下激光引信优化设计提供参考.     

稳健声线扰动特征用于浅海小目标定位*

针对海洋环境中的信道起伏变化对基于扰动声线声压敏感核的水下小目标定位算法影响较大的问题,提出了基于稳健声线扰动特征的目标定位方法,该方法首先对海洋环境中接收声场的到达结构进行分析,提取稳态的到达成分;然后通过观测稳健声线对应的接收信号在目标穿越过程中的扰动特征提取扰动声线;最后应用扰动声线类定位方法得到水下目标的定位模糊图实现定位。在浅海港口环境中开展了蛙人穿越实验,发射信号为中心频率为22.5kHz,带宽为15kHz的线性调频信号,实验数据的处理结果表明,直达路径和一次水底反射路径受信道起伏的影响较小,通过筛选稳健声线可以将扰动声线的定位方法用于自然的海洋环境。     

水中分层弹性球壳高频时域回波的声学编码研究

针对水下集群目标及敌我目标识别的难题,该文提出了一种基于水中分层弹性球壳高频时域回波的声学编码原理及方法。推导了水中4层弹性球壳目标散射声压的简正级数解,并与有限元结果进行了对比验证。通过构造高频主动声呐的探测脉冲信号,与4层弹性球壳声传递函数的简正级数解做卷积运算,获得了目标的时域回波脉冲序列。研究了分层弹性球壳的厚度、各层材料属性、排布顺序等对时域回波特征的影响规律,提出了基于时域回波特征的声学编码方法。研究表明：利用水中分层弹性球壳目标高频时域回波特征能够实现声学编码,回波结构稳定,且不受限于探测方向。通过携带或安装这种分层弹性球壳结构,有望识别水下航行体/悬浮体等目标。该文的研究对水下目标的主动探测身份识别及导航等具有一定的参考价值。     

十七无十字阵水下合作目标远程定位方法

结合水声对抗的实际需求,针对海洋环境下目标定位困难且定位距离有限的问题,利用多水听器十字阵接收信号,并对信号进行加权来提高接收信号信噪比,以达到定位水下合作目标的目的。具体通过波束形成和信号相关,依据目标方位与波束形成方位一致时能量最大的原则,实现对远距离水下合作目标方位和距离的估计,并通过仿真和试验验证了所提定位方法的有效性。     

水下目标声散射信号的时频域盲抽取

目标声散射机理及其散射特性为识别目标的物理依据.针对水下目标声散射成分在时-频域存在相互混叠干扰,造成目标弹性声散射特征不稳定的问题,提出一种适合在欠定问题下分离目标声散射成分的时频域盲抽取方法.研究声散射成分的时频特征差异,构造目标回波单源自项的空间时频分布矩阵,通过对其进行特征值分解抽取相应的声散射成分,建立描述目标声散射物理特性的信号模型.抽取出的目标各弹性波分量与以表面环绕波产生理论计算结果相符.仿真与消声水池实验数据处理结果表明,该算法可以分离出目标回波的各个声散射成分,提高了分离信号的输出信噪比,为水下目标识别提供稳定和可靠的特征.     

基于激光水下爆炸声源的声探测技术

基于激光水下爆炸的声探测技术,设计了激光声水下目标探测器。对激光水下爆炸声源的产生机理进行研究,并开展水下探测器发射声信号检测的实验。实验结果表明:强脉冲激光聚焦于水介质产生爆炸性球面声源,探测器内部的声反射面将球面声信号转变为高指向性的平面波信号。通过对探测器的发射信号和接收的目标回波信号进行数值计算,得到探测器发射信号具有波束指向性窄、距离分辨力高和探测距离远等特点,满足水下目标探测的应用需求。     

噪声背景下双输入时延混合系统的盲源分离

噪声背景下应用盲分离技术恢复源信号是盲信号处理的难点之一,本文主要研究了双输入时延有噪混合模型的盲分离方法,和传统的盲分离算法相比,该方法可以有效地利用多阵元的观测信号,对加性噪声具有相当的抑制作用。     

一种异步非正交跳频网台盲分选方法

提出了一种新体制跳频网台盲分选方法,针对跳频通信异步非正交组网方式,将基于最大信噪比算法的盲源分离技术应用于跳频网台分选。建立了跳频网台盲分选仿真数学模型并进行了多跳频网台分选仿真。仿真结果验证了盲源分离技术应用在跳频网台分选中的可行性和有效性,得出了跳频网台盲分选方法对异步非正交组网方式的分选性能。     

固定干扰源存在下的管道泄漏检测和准确定位

为了解决固定位置的声/振动干扰源引起的管道泄漏声检测的虚警或者漏点定位错误问题,利用泄漏信号源和固定干扰源之间的独立性,通过盲卷源分离算法得到泄漏信号在一定代价函数下的最优估计,并将该估计作为输入信号从检测信号中自适应预测得到泄漏信号,这样就可以保留泄漏信号中的时延信息。对实际检测信号的处理表明,应用提出来的方法可以有效的去除检测信号中来自固定干扰源的噪声,同时不损失泄漏信号中的时延信息,可在固定干扰源存在时实现管道泄漏有效检测和准确定位。      

混沌信号在无线传感器网络中的盲分离

混沌信号在本质上属于非线性非高斯信号,它在无线传感器网络下的应用还涉及到信号量化问题,这使得混沌信号在此应用环境下的信号盲分离更为棘手.针对此问题,本文在容积卡尔曼粒子滤波的框架下提出一种解决方法.文中首先推导出观测信号的概率密度函数,在量化比特有限的情况下,采用最优量化器,获得最优的量化结果.在此基础上,使用容积卡尔曼滤波器产生粒子滤波中的重要性概率密度函数,融入最新的观测值,提高粒子对系统状态后验概率的逼近,提高信号盲分离的精度.仿真结果表明算法能够有效地分离混合混沌信号,参数估计的精度及其运算量均优于已有的无先导卡尔曼粒子滤波算法,其运行时间为无先导卡尔曼粒子滤波算法的88.77%.     

基于最大信噪比测量两相流速度

为了克服噪声对信号的影响,提出一种利用最大信噪比和相关法测量两相流速度的方法.基于最大信噪比的信号分离方法是一种盲源信号分离方法,该算法利用统计独立信号完全分离时信噪比最大作为分离准则,它具有非常低的计算复杂度.这里首先利用盲源信号分离方法分别提取出上游和下游两相流信号,并据此求出两相流信号的相关函数曲线,由此求出信号的渡越时间,最后给出仿真实验的处理结果.实验结果表明该方法能够满足两相流速度的测量要求.     

Direction of arrival estimation for underwater acoustic target based on compressed sensing after blind reconstruction of array signal in frequency domain

The performance of direction of arrival(DOA) estimation based on compressed sensing(CS) decreases in the complex ocean marine environment.In order to tackle this problem,a method of DOA estimation for underwater acoustic target based on CS after blind reconstruction of array signal in frequency domain is proposed.Firstly,the received array data are transformed to frequency domain by Fourier transform and frequency domain wideband signal are divided into part overlapping multiple sub-band array signal.Secondly,each subband array signal are separated using plural blind source separation(BSS) method,the sub-band separated matrix and target signal can be estimated.Thirdly,the array signal in frequency domain are reconstructed according to the separated matrix and separated signals which were not noises.Fourthly,the sub-band spatial spectrum corresponding to the reconstructed array signal is obtained by CS beamforming method.Finally,the total spatial spectrum is achieved by summing the all sub-band spatial spectrum.And the target direction can be estimated by searching the peak value of the total spatial spectrum.The verification results of simulator data and sea measured data show that,under the same conditions,the target detection ability and direction precision of the proposed method is superior to the classical minimum variance distortionless response(MVDR) method,frequency domain CS method,BSS combined with MVDR method.The spatial spectrum energy of faint target signal is improved obviously,and the ability of the sonar to detect faint target is enhanced.     

Blind speech source separation via nonlinear time-frequency masking

Aim at the underdetermined convolutive mixture model, a blind speech source separation method based on nonlinear time-frequency masking was proposed, where the approximate W-disjoint orthogonality （W-DO） property among independent speech signals in time-frequency domain is utilized. In this method, the observation mixture signal from multimicrophones is normalized to be independent of frequency in the time-frequency domain at first, then the dynamic clustering algorithm is adopted to obtain the active source information in each time-frequency slot, a nonlinear function via deflection angle from the cluster center is selected for time-frequency masking, finally the blind separation of mixture speech signals can be achieved by inverse STFT （short-time Fourier transformation）. This method can not only solve the problem of frequency permutation which may be met in most classic frequency-domain blind separation techniques, but also suppress the spatial direction diffusion of the separation matrix. The simulation results demonstrate that the proposed separation method is better than the typical BLUES method, the signal-noise-ratio gain （SNRG） increases 1.58 dB averagely.     

Emulsion droplet sizing using low-field NMR with chemical shift resolution and the block gradient pulse method

Pulsed Field Gradient (PFG) measurements are commonly used to determine emulsion droplet size distributions based on restricted self-diffusion within the emulsion droplets. Such measurement capability is readily available on commercial NMR bench-top apparatus. A significant limitation is the requirement to selectively detect signal from the liquid phase within the emulsion droplets; this is currently achieved using either relaxation or self-diffusion contrast. Here we demonstrate the use of a 1.1 T bench-top NMR magnet, which when coupled with an rf micro-coil, is able to provide sufficient chemical shift resolution such that unambiguous signal selection is achieved from the dispersed droplet phase. We also improve the accuracy of the numerical inversion process required to produce the emulsion droplet size distribution, by employing the Block Gradient Pulse (bgp) method, which partially relaxes the assumptions of a Gaussian phase distribution or infinitely short gradient pulse application inherent in current application. The techniques are successfully applied to size 3 different emulsions.     

A new efficient two-channel backward algorithm for speech intelligibility enhancement: A subband approach

This paper addresses the problem of speech intelligibility enhancement by adaptive filtering algorithms employed with subband techniques. The two structures named the forward and backward blind source separation structures are extensively used in the speech enhancement and source separation areas, and largely studied in the literature with convolutive and non-convolutive mixtures. These two structures use two-microphones to generate the convolutive/non-convolutive mixing signal, and provide at the outputs the target and the jammer signal components. In this paper, we focus our interest on the backward structure employed to enhance the speech signal from a convolutive mixture. Furthermore, we propose a subband implementation of this structure to improve its behavior with speech signal. The new proposed subband-Backward BSS (SBBSS) structure allows a very important improvement of the convergence speed of the adaptive filtering algorithms when the subband-number is selected high. In order to improve the robustness of the proposed subband structure, we have adapted then applied a new criterion that combines the System Mismatch and the Mean-Errors criterion minimization. The proposed subband backward structure, when it is combined with this new criterion minimization, allows to enhance the output speech signal by reducing the distortion and the noise components. The performance of the proposed subband backward structure is validated through several objective criteria which are given and described in this paper.     

车载场景结合盲源分离与多说话人状态判决的语音抽取

在车载分布式传声器阵列场景中,结合盲源分离TRINICON (Triple-N ICA for convolutive mixtures)算法与多说话人状态判决实现期望语音抽取。根据分布式传声器阵列与声源的相对位置关系,设计特定的盲源分离初始化条件以保证输出通道与声源的映射关系;根据分布式传声器阵列的频响特点,设计特征矢量来进行多说话人判决,并将判决结果引入TRINICON算法参数迭代过程。在使用实际车载录音数据的仿真评测中,所提方法在不同信噪比下有较高的鲁棒性,可有效提升TRINICON算法的收敛速度和语音信号的信扰比,且可以确保准确的通道映射。评测结果表明该方法可以在车载场景中有效抽取出期望语音,为车载复杂场景下的声信息提取提供了一种可靠且收敛快速的解决方法。