非均匀混响统计建模与功率估计

针对非均匀混响中进行恒虚警(CFAR)检测所需的背景功率估计问题,通过对非均匀混响进行统计建模分析,提出一种非均匀混响功率自适应估计方法。所提方法基于排序统计、功率分类等处理,对混响数据服从的统计模型进行判别,根据均匀混响、参杂强干扰混响、混响边缘等具有不同特性的混响成分,选择不同的处理方式进行功率估计。进一步将所提出的混响功率估计方法应用于CFAR检测中,获得一种新的CFAR检测器。仿真和实测混响数据的处理结果表明,提出的混响功率估计方法可以对强干扰和混响边缘等非均匀混响背景进行有效判别和功率估计,提出的CFAR检测器有效提高了非均匀混响背景中的目标检测性能。      

一种检测低信噪比下未知波形时变相干信号的方法*

从获取的数据中检测目标信号，是雷达、声呐等领域重要的研究内容。时频域严重畸变的回波信号以及时变线谱信号的自适应检测，具有重要意义。为了挖掘和推广自适应相干累积（Adaptive Coherent Integration，ACI）技术在未知时变信号检测领域的能力，本文给出了ACI算法的基本原理，并进行了系统性地理论推导，得到了ACI算法的宽带时变自回归滑动平均模型（ARMA）和窄带复解析模型。利用这些模型解释了产生信号相干累积的机理，分析得出了产生相干累积的条件，揭示了这种时变系统的许多奇异特性。结合仿真实验和实际海上实验数据对ACI算法展开验证，结果表明ACI算法对于低信噪比下未知波形信号具有优异的检测能力，展示出ACI算法在水下探测等相关领域存在广泛的实际应用前景。     

自适应线谱干扰抵消器的性能及其非维纳滤波现象

自适应滤波器的性能通常采用维纳滤波器理论来分析,本文指出自适应线谱干扰抵消器不符合经典解的现象。在对权系数的动态分析中,揭示了非维纳滤波效应产生的机理。     

球谐域自适应混响抵消与声源定位算法

提出了一种基于球谐域的自适应混响抵消与声源定位算法,该方法通过去混响处理改善语音质量,并提高球谐域定位算法在混响环境下的定位性能。推导了基于多通道线性预测的自适应混响抵消算法在球谐域的表达式,针对刚球模型提出分阶处理的去混响方法,并对去混响后的信号进行波达方向估计。采用32元球阵的仿真结果表明,相比于球谐域不分阶去混响方法,该方法最大可减少约2/3的运算量,同时语音PESQ得分及SRMR均显著提高。利用实验数据对算法性能进行测试,实验结果验证了该方法在实际声学环境中去混响和声源定位的有效性。      

基于改进卡尔曼滤波的水声通信盲自适应多用户检测算法

针对水声通信网络中遇到的多用户检测中目标用户的多址干扰等检测问题,提出了基于改进Kalman算法的盲自适应多用户检测算法,解决了多用户检测中的多址干扰对水声通信信道用户变动时的干扰抑制问题。仿真分析分别针对同步多用户、异步多用户通信过程,对比了传统Kalman算法及改进的Kalman算法的性能差异,通过仿真对比表明,改进后的Kalman检算法不需要训练序列即可以实现同步和异步通信状态下的多水声目标用户的盲自适应检测,改进后的算法目标检测的信干比比传统算法最大可提高6dB。新算法对于水下多用户检测、区分,准确、稳定的实现基于CDMA协议的快速水声通信具有重要意义。     

海洋混响信号的自适应非线性预测

基于非线性动力学对海洋混响建模,提出了一种自适应非线性预测方法,通过设计一个滤波器来逼近混响信号在相空间的演化轨迹;采用在不同海域进行的两次海上实验获取的混响信号,对自适应预测方法进行验证,其单步预测结果与实验信号符合较好;以模型的单步预测误差作为检验统计量来检测混响中的目标回波,可以在一定程度上抑制混响干扰,提高信混比.     

一种采用脉冲串的自适应有源干扰抵消器

在许多应用中，周期性干扰是由旋转的机械设备所产生的。一个周期性信号可以与一个特殊形式的周期性的脉冲串完全相干。本文提出了一种采用脉冲串的自适应有源噪声抵消器(AANC)来抵消周期性干扰，这种抵消器产生一个与干扰信号相同步的周期性的单位脉冲串作为参考输入。将这种有源噪声抵消器和Delayed-X LMS算法相结合，可以大大地减小运算量，并且也可以保证良好的收敛特性。理论分析和计算机仿真验证了本文的结果。     

光纤激光自混合散斑远程测速研究

推导出了等效Fabry-Perot腔输出光强的表达式,结合Labview和Matlab软件编写了自适应噪声抵消器.提出了将自适应噪声抵消器应用到激光散斑信号的去噪处理,并通过计算散斑频谱能量密度推算出了被测目标的速度.基于Labview软件编写了监控程序,通过以太网实现了远程控制激光散斑信号对运动物体速度的实时测量.     

基于引导滤波和分块自适应阈值的单帧红外弱小目标检测

为了在有效地检测复杂场景下红外弱小目标的同时保持较低虚警率,在满足算法实现实时性的前提下,提出一种基于引导滤波和分块自适应阈值的单帧红外弱小目标检测。首先,为缓解边缘杂波干扰,采用具有保边特性的引导滤波对图像进行背景估计;然后,利用弱小目标具备的局部灰度最大特性,提出基于软阈值非极大值抑制的九宫格滤波计算目标的概率。通过加权的方式进一步剔除背景,抑制结果中不满足目标特性的区域;最后,针对复杂场景目标检测虚警率和漏检率高的问题,提出一种分块自适应阈值分割方法提取候选目标。实验结果表明,在公开数据集上与Top-Hat、LCM和Max-Median等经典方法相比,所提方法性能优于其他方法,恒虚警下不同复杂度场景的召回率分别达到87.97%、84.93%和86.22%,可有效抑制背景,增强目标信号,提高红外弱小目标检测的召回率,且具有更好的场景鲁棒性。     

红外搜索系统中弱小目标检测算法研究

 复杂背景下低信噪比弱小目标的检测是红外搜索系统中的重点和难点,为解决红外搜索系统中杂波干扰多、目标信噪比低等问题,提出一种模板匹配滤波的目标检测方法。该算法在预测背景的同时,通过对图像背景灰度值进行动态的阈值处理,自适应地进行背景抑制。当背景包含较多复杂因素时,采用模板匹配滤波的目标检测方法,消除背景抑制后的残留杂波,实现弱小目标的提取。试验结果表明：当场景较复杂且图像信噪比较低时,使用该算法处理后可使图像信噪比达到4 dB以上,从而提高了弱小目标的检测概率。     

改进次最佳检测在侧扫声呐底混响抑制中的应用*

侧扫声呐进行沉底小目标探测时,底混响是主要背景干扰。底混响通常是一种非平稳、非高斯的带限噪声,它使得白噪声条件下的滤波器性能受到限制。在混响背景下常利用自回归模型对接收信号进预行白化处理,但对于实际侧扫声呐应用,白化后直接匹配滤波的处理效果不甚理想。针对此问题,在自回归模型预白化的基础上,提出采用一种次最佳检测与多分辨二分奇异值分解相结合的改进方法。该方法首先对接收信号进行分段处理,利用改进Burg算法估计每段数据自回归模型的系数及阶数;然后构造白化滤波器对分段数据预白化,并对白化后的数据进行多分辨二分奇异值分解;最后应用ostu方法对原始声图和处理后的声图进行目标检测。仿真与实验结果表明,该方法明显提高了信混比,改善了侧扫声呐沉底静态小目标的成图质量,有利于后期实现基于图像的目标自动检测。     

Performance of an adaptive beamforming noise reduction scheme for hearing aid applications. II. Experimental verification of the predictions

A method to predict the amount of noise reduction which can be achieved using a two-microphone adaptive beamforming noise reduction system for hearing aids [J. Acoust. Soc. Am. 109, 1123 (2001)] is verified experimentally. 34 experiments are performed in real environments and 58 in simulated environments and the results are compared to the predictions. In all experiments, one noise source and one target signal source are present. Starting from a setting in a moderately reverberant room (reverberation time 0.42 s, volume 34 m3, distance between listener and either sound source 1 m, length of the adaptive filter 25 ms), eight different parameters of the acoustical environment and three different design parameters of the adaptive beamformer were systematically varied. For those experiments, in which the direct-to-reverberant ratios of the noise signal is +3 dB or less, the difference between the predicted and the measured improvement in signal-to-noise ratio (SNR) is -0.21+/-0.59 dB for real environments and -0.25+/-0.51 dB for simulated environments (average +/- standard deviation). At higher direct-to-reverberant ratios, SNR improvement is systematically underestimated by up to 5.34 dB. The parameters with the greatest influence on the performance of the adaptive beamformer have been found to be the direct-to-reverberant ratio of the noise source, the reverberation time of the acoustic environment, and the length of the adaptive filter.     

空时多普勒频移域运动小目标的抗干扰探测方法

有源声呐使用多普勒敏感信号可在多普勒频移域分离杂波、混响等干扰和运动目标,但低信干比时强干扰的时间旁瓣泄露和多普勒旁瓣泄露会淹没弱目标.针对该问题,提出了一种基于自适应最小均方(LMS)算法和宽带模糊函数(WAF)的运动小目标抗干扰探测方法.首先在空间多普勒频移域上利用基于LMS的自适应陷波器抑制干扰,然后在快时间多普...     

Performance of an adaptive beamforming noise reduction scheme for hearing aid applications. I. Prediction of the signal-to-noise-ratio improvement

Adaptive beamformers have been proposed as noise reduction schemes for conventional hearing aids and cochlear implants. A method to predict the amount of noise reduction that can be achieved by a two-microphone adaptive beamformer is presented. The prediction is based on a model of the acoustic environment in which the presence of one acoustic target-signal source and one acoustic noise source in a reverberant enclosure is assumed. The acoustic field is sampled using two omnidirectional microphones mounted close to the ears of a user. The model takes eleven different parameters into account, including reverberation time and size of the room, directionality of the acoustic sources, and design parameters of the beamformer itself, including length of the adaptive filter and delay in the target signal path. An approximation to predict the achievable signal-to-noise improvement based on the model is presented. Potential applications as well as limitations of the proposed prediction method are discussed and a FORTRAN subroutine to predict the achievable signal-to-noise improvement is provided. Experimental verification of the predictions is provided in a companion paper [J. Acoust. Soc. Am. 109, 1134 (2001)].     

正交多相码连续波主动声呐回波检测算法设计*

与常规脉冲式主动声呐相比,连续波主动声呐能够提高目标回波的时间处理增益和目标信息更新速率。本文提出一种由正交多相码合成的连续发射波形,分析了发射信号和目标回波模型,设计了多通道匹配滤波器组完成回波检测。为了进一步提高接收机检测性能,提出了多通道非相干积累的处理方法。通过数值仿真,分析提出的连续波形的多普勒分辨性能和目标信息更新率。通过蒙特卡罗法获取ROC曲线,比较了脉冲式主动声呐和连续波主动声呐在均匀混响背景下对单目标检测性能的差异。仿真结果表明,本文设计的连续波波形具有较好的多普勒分辨性能,在均匀混响背景下,回波检测算法能够明显提高单个目标的探测能力。     

利用正弦调频信号的宽带速度敏感特性抑制混响

有源声呐探测水中低速目标时,混响与目标回波的频率接近,目标回波与混响分离困难.根据运动目标与产生混响的散射体在速度域的差异,利用正弦调频信号(SFM)的速度敏感特性实现目标回波与混响的有效分离.推导了 SFM信号宽带混响抑制能力与速度分辨模糊之间的约束关系,建立了波形优化设计的搜索模型.通过多普勒滤波处理将数据从频率域...     

Blind dereverberation in the deep sea

Experimental data are presented on the blind dereverberation of the noise-type signal generated by a sound source moving in the deep sea. The noise emitted by a towed source is received by a drifting hydrophone with a high excess of the signal over the ambient noise, which results in a stable interference pattern of high contrast. The observed interference structure indicates that the signal arrives at the receiver along different paths. With the use of the blind dereverberation technique for the signal processing and without any a priori information on the properties of the propagation channel, the parameters (the delay, the amplitude, and the phase) of each of the seven interfering signals are determined. From the data obtained, the frequency response of the filter that provides a strong suppression of the reverberation is calculated and the spectrum of the received signal is obtained without any interference distortions.     

水下目标回波与混响的时频形态特征域盲分离

水下沉底或掩埋目标识别受海底混响干扰严重,并且目标回波与混响在时-频域上均存在混叠,增大了对目标回波与混响的分离难度。根据目标回波与混响的产生机理差异,将图像形态学与时频分析相结合的盲分离算法用于目标回波与混响的分离。推导了目标几何声散射成分与混响在Wigner-Ville时频面的形态特征表达式,利用图像形态学滤波去除Wigner-Ville时频面中的混响及刚性亮点之间交叉项,在时频形态特征域获取解混矩阵,实现了目标回波和混响的分离。仿真与实验数据处理结果表明,结合图像形态学的时频域盲分离算法提高了目标回波信号的信混比。      

水声信号稀疏重构高分辨角度-多普勒成像

针对傅氏空时二维谱估计分辨率低以及声呐空时采样数据样本数不足给角度-多普勒成像带来困难的问题,提出一种水声信号稀疏重构的高分辨角度-多普勒成像方法和抗混响空时滤波器的稀疏重构方法。该方法在声呐阵列单测量向量的极少观测样本条件下,建立阵列信号的空时稀疏表示模型,应用稀疏表示的匹配追踪算法和基追踪算法重构回波与混响的高分辨角度-多普勒像。并根据运动声呐回波与混响的空时分布规律及声呐待检测距离单元位置的先验信息,沿着混响空时分布脊线设计混响稀疏表示的专用空时导向向量字典,通过重构抗混响空时滤波器来抑制角度-多普勒平面的混响干扰。对运动声呐前视和侧视阵列的计算机仿真结果表明,在混响背景中,该方法采用声呐阵列单测量向量重构了低速运动目标多亮点回波的高分辨角度-多普勒像,频率分辨率突破傅里叶分辨率,角度分辨率突破阵列瑞利限,分辨率明显优于傅氏空时谱估计。      

Estimation of coherent detection performance for spread scattering in reverberation-noise mixtures

Narrow-band matched filter processing gain is estimated for medium- and high-frequency active sonars for which the random backscattering processes are assumed to be wide sense stationary in time frequency and uncorrelated in delay-Doppler wide sense stationary and uncorrelated scattering [WSSUS conditions]. Echo and reverberation processes that are WSSUS are described by two-dimensional scattering functions defined in the delay-Doppler plane. The average receiver responses are estimated from the convolution of the appropriate scattering function with the waveform ambiguity function. Estimates of matched filter processing gain are derived for continuous wave (CW) linear frequency modulation (LFM), and discrete frequency shift keyed (FSK) (hop code) waveforms reflected from point and uniform delay spread scatterers masked by reverberation. These bound matched filter performance for a particular waveform and interference distribution since most delay spread scattering falls somewhere between these extremes. The scattering and ambiguity functions are modeled by bounded constant amplitude functions in delay-Doppler that permit the convolutions to be approximated by overlapping area calculations. The results are presented in tabular form as simple formulas that are functions of the reverberation, noise, and waveform parameters. The estimates are shown to be consistent with processing gain measurements made from multiple realizations of synthesized and in-water data.