一种基于模滤波的水面干扰抑制方法研究

水面离散干扰源严重影响了声呐对水下目标的检测和定位性能。提出了一种基于模滤波的水面干扰抑制技术。该技术利用水面声源和水下声源激发的简正波模态特性的差异,在初步估计出干扰源位置的基础上,结合模波束形成实现水面离散干扰源的抑制。针对典型的浅海波导环境,进行了计算机仿真实验,验证结果表明:该技术在水面离散干扰源和目标声源位置未知的情况下,实现了水面离散干扰抑制和水下目标定位。较其它方法相比,该技术能自动选择相应的模态滤波器,在抑制水面离散干扰源的同时,保证了水下目标的定位精度。     

一种有效抑制阵列后方声源的心形指向性传声器阵列

基于心形指向性传声器的波束形成可以有效抑制阵列后方声源的干扰,提高前方声源的识别精度。以平面轮形传声器阵列为对象,借助MATLAB仿真计算,对阵列后方声源波束形成声源识别特性及其抑制方法进行研究。基于除自谱的互谱波束形成算法提出了含有传声器指向性的波束形成算法,对圆形和心形指向性传声器进行不同声源类型的波束形成仿真计算,并针对仿真结果显示出的不足,给出了既能保证阵列平面上最大声压贡献量的识别精度,又能降低旁瓣水平的幅值校正算法。试验结果证明了基于心形指向性传声器的波束形成可以有效抑制后方声源。     

阵列信号维纳滤波用于主动声呐图像增强处理

声呐图像的噪声背景抑制是提高水下目标检测能力的重要问题。针对声呐图像背景斑点噪声强、目标轮廓模糊、目标回波对比度低等问题,利用确定性目标回波信号与随机分布的干扰噪声之间的相关统计特性差异,采用基于最小均方差准则的阵列信号维纳滤波器,通过主动最小方差无畸变响应（Minimum Variance Distortionless Response,MVDR）波束形成和后置维纳滤波的两级处理,去除声呐随机噪声背景。试验数据的处理结果表明：在噪声干扰条件下,相比于常规波束形成（Common Beamforming,CBF）,主动MVDR处理提高了目标回波的局部信噪比,后置维纳滤波处理降低了随机分布的斑点噪声,使声呐图像的清晰度得到增强。     

基于干扰抑制方法和引导声源的水平阵被动目标测距

基于引导声源的被动测距由于其对环境参数较少的要求受到了广泛关注。而处于浅海复杂环境下的被动声呐中,目标信号的声场干涉结构可能被邻近方位上的强干扰的旁瓣掩盖或改变,影响最终的测距精度。首先利用基于特征分解的自适应干扰抑制方法对强干扰环境中的接收信号进行干扰抑制,获得更高信噪比和信干比的目标信号;然后采用自适应的最小方差无失真波束形成器方法进行水平阵波束形成,得到更精确的目标声源声场干涉结构;其次基于干涉条纹的波导不变量特点,利用引导声源与目标声源干涉条纹的关系进行目标声源被动测距。实验结果验证了该方法的有效性和应用的可行性。     

一种基于特征分析的强干扰抑制方法

水声环境中微弱目标往往被掩盖在强干扰的旁瓣中而无法检测。研究如何抑制强干扰,提高输出信噪比,对提高声呐探测性能具有重要意义。假设干扰能量远大于目标信号能量。首先,对接收数据协方差矩阵进行特征分解,其中最大特征值对应的特征向量属于干扰特征向量。然后利用正交投影方法将阵列接收数据向干扰子空间的正交子空间投影,将干扰数据去除,从而达到抑制强干扰的目的。数值仿真和海试数据验证结果表明,该强干扰抑制方法能够很好地抑制强干扰,提高目标信号输出信噪比和目标方位估计可靠性,可为后续的目标被动定位创造有利条件。     

波束形成三维传声器阵列声源识别的改进方法

采用具有倾角的轮型阵列能消除平面阵列对其后方背景声源无抑制能力的缺点,降低对测试环境的要求。通过仿真计算获得了三维轮型传声器阵列波束形成指向图及典型最大旁瓣水平随阵列倾角的变化曲线,分析了阵列倾角对其声源识别性能的影响。在此基础上,提出了阵列多倾角测量声级平均的声源识别改进方法,三种类型声场声源识别的模拟计算结果表明：该方法在准确计算目标声源位置和幅值的同时,相比于一定倾角阵列的单次测量结果可以更有效地同时衰减阵列前方声波和背后背景噪声在聚焦方向上产生的旁瓣干扰,显著地提高了声源识别精度。     

低信噪比环境下语音识别的鲁棒性方法研究

针对噪声环境下语音识别率急剧下降的问题，提出了一种基于语音时频域稀疏性原理的改进最小方差无畸变响应波束形成与改进维纳滤波结合的算法。该算法首先利用麦克风阵列语音信号的空间信息，通过基于时频掩蔽的改进最小方差无畸变响应波束形成器，增强目标声源方向的语音信号，抑制其他方向噪声的干扰，然后再使用改进的维纳滤波器去除残留噪声并提高语音可懂度，对增强后的语音信号提取梅尔频率倒谱系数作为特征参数，使用隐马尔可夫模型搭建语音识别系统。实验结果表明，该方法能够有效提高低信噪比环境下的语音识别率，具有较好的鲁棒性。     

自适应插值空域矩阵滤波器设计

针对基于常规插值矩阵滤波的高分辨方位估计算法当非插值区域存在强声源信号时性能严重降低的问题,提出了一种自适应插值空域矩阵滤波器的设计方法.该方法在保证插值误差和非插值区间滤波响应低于设定值的条件下,最小化插值空域滤波后的输出功率,使得插值矩阵滤波器能尽量保证让插值阵列流形逼近于规定的虚拟阵列流形,同时抑制非插值区间(阻带)的干扰和噪声.将滤波器的优化设计问题表达成二阶锥规划的形式,利用已有的内点方法求出其数值解.仿真结果验证了该方法的有效性.     

基于移动麦克风阵列的稳态声源识别

基于波束形成的麦克风阵列声源识别技术存在识别低频声源分辨率低、识别高频声源易产生空间混叠的问题,影响了声源识别的准确性。对于稳态声源,本文提出两种麦克风阵列移动方法,即改变麦克风阵列中心位置、调整测量距离来提高低频声源识别分辨率,和采用旋转麦克风阵列进行多次测量的方法来抑制高频声源识别中的空间混叠,从而达到使用较少麦克风提高声源识别性能的目的,并通过仿真和实验验证了此方法的有效性。     

圆阵双基地声纳直达波抑制技术研究

以圆阵为双基地声纳接收阵列流形,提出了一种新的基于多重信号分类(MUSIC)技术的波束形成及零点抑制算法。在理论分析了第一类零点约束条件的基础上,提出了第二类零点(高阶零点)约束条件。给出两类零点约束条件干扰抑制能力的比较。仿真结果表明,该算法可有效接收目标回波信号且屏蔽直达波强干扰。讨论干扰达波方向(DOA)与阵元数对算法直达波抑制能力的影响,以及多源干扰条件下算法的干扰抑制能力。     

基于单矢量水听器空间谱增强的MUSIC算法

针对单矢量水听器多重信号分类(Multiple Signal Classification,MUSIC)算法在低信噪比条件下,存在谱峰宽度变宽、估计精度变低等性能恶化的问题,提出一种基于单矢量水听器空间谱增强的改进MUSIC算法。该算法的基本原理是:单声源入射到单只矢量水听器上时,加一参考信号源,若两者方位相同,则同方位叠加使空间谱增强;若两者方位不相同,则两方位合成,使空间谱估计产生偏差。因此,改变参考信号源的方位,当参考信号源的方位与信号源的方位一致时,将使谱峰得到增强,此时空间谱达到最大值,其对应的角度即为信号源的方位角。仿真分析及实验数据处理结果表明,与常规MUSIC算法相比,该算法具有更尖锐的谱峰、更高的估计精度,能够实现更好的空间谱估计。     

水下小孔径阵列远程目标检测方法研究

匹配滤波器频域自适应线谱增强方法是一种基于递归算法的非线性滤波技术,它大大提高了匹配滤波器的检测性能.针对当前该技术使用窄带信号作为发射信号存在可利用的带宽有限,不能充分发挥自适应线谱增强器性能的问题,文章提出将该技术与宽带信号相结合来检测远程目标.仿真显示,该方法在低信噪比条件下获得了较高的信噪比增益和检测概率.海试...     

Ultrasonic nondestructive evaluation of highly scattering materialsusing adaptive filtering and detection

Adaptive filtering and detection has been applied to the problem of detecting ultrasonic echo signals from test targets where the wanted signals are masked by coherent scattering from grain boundaries present in highly scattering materials. The filter is based on the normalized least mean square (LMS) error algorithm, and can be operated with either an independent reference signal or by using the delayed input signal as the reference. Tests made on a collection of 64 ultrasonic A-scans using the same processing parameters show that an up to 10 dB improvement in signal-to-noise ratio can typically be obtained. A cell-averaging constant false alarm rate (CFAR) detector is used to detect the signals automatically. The performance of the method is compared to that of split spectrum processing, both with and without polarity thresholding     

单矢量水听器二维DOA估计算法

为了减小传统声压阵的布阵规模,提高传统声压阵的测量精度,利用矢量水听器的阵列流形特性,使用阵列信号处理的原理进行二维DOA估计。将单个矢量水听器理解成一个声压水听器和三个振速水听器组成的阵列,在无需知道信号先验知识的条件下,分别采用MUSIC算法和ESPRIT算法对多个不相关的单频窄带信号的二维DOA进行了估计。仿真结果表明:在高信噪比情况下,两种算法的精度都很高,优于5阵元的声压平行线阵。利用单矢量水听器能够对信号的二维到达角进行有效估计,远小于传统声压阵的布阵规模。     

The dynamic range tester: a multipurpose “real-world”signal simulator for correlator testing and other applications

The dynamic range tester (DRT) is a patented prototype system that functions as a dual-channel, precision signal-to-noise ratio (SNR) generator. It was designed for testing high-speed acousto-optic correlators, and can be used for many applications requiring “real-world” test signals. The DRT is a convenient tool for generating two highly isolated, noisy test signals from a single signal source, to simulate two antennas receiving the same signals. By splitting a user-supplied signal into two copies and adding wideband, random noise to each portion, the DRT generates two noisy test signals, one in each channel. The noise generated in one channel of the DRT is uncorrelated and isolated from the noise generated in the other channel by approximately 90 dB. The correlated (signal) and uncorrelated (noise) parts of the test signals are each variable over a wide dynamic range. The DRT is useful for a variety of testing and demonstration purposes: generally, for evaluating a system's tolerance to noisy inputs and specifically, for making measurements of dynamic range, processing gain, and frequency resolution of a correlator, spectrum analyzer, or other signal processing system. The DRT can also use two signal sources, one in each noisy channel, to simulate two antennas receiving different signals. This configuration of the DRT may be useful for performing interference and bandwidth testing of signal processing hardware. The patented design is extendible to all frequency ranges, perhaps for producing useful instrumentation in such fields as telecommunications, telemetry, biomedical engineering, etc     

Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection

The utilization of signal processing techniques in nondestructive testing, especially in ultrasonics, is widespread. Signal averaging, matched filtering, frequency spectrum analysis, neural nets, and autoregressive analysis have all been used to analyze ultrasonic signals. The Wavelet Transform (WT) is the most recent technique for processing signals with time-varying spectra. Interest in wavelets and their potential applications has resulted in an explosion of papers; some have called the wavelets the most significant mathematical event of the past decade. In this work, the Wavelet Transform is utilized to improve ultrasonic flaw detection in noisy signals as an alternative to the Split-Spectrum Processing (SSP) technique. In SSP, the frequency spectrum of the signal is split using overlapping Gaussian passband filters with different central frequencies and fixed absolute bandwidth. A similar approach is utilized in the WT, but in this case the relative bandwidth is constant, resulting in a filter bank with a self-adjusting window structure that can display the temporal variation of the signal's spectral components with varying resolutions. This property of the WT is extremely useful for detecting flaw echoes embedded in background noise. The detection of ultrasonic pulses using the wavelet transform is described and numerical results show good detection even for signal-to-noise ratios (SNR) of -15 dB. The improvement in detection was experimentally verified using steel samples with simulated flaws.     

水下声信标信号的多脉冲匹配滤波改进方法

水下声信标信号检测是搜寻黑匣子的重要技术之一。针对水下声信标信号声源级低、脉冲宽度窄所带来的检测难题,充分利用声信标信号周期短、相邻脉冲信号相关性强等特点,提出了一种基于多脉冲积分的改进匹配滤波方法,通过前后脉冲匹配方法克服标准信号匹配处理中因信号畸变带来的匹配处理增益下降,通过多脉冲累积提高积分增益。通过仿真实验验证,当取多脉冲累积数为6时,在理想白噪声环境下,所提改进方法比传统单脉冲匹配滤波检测性能提高约4 dB,特别是在存在明显多普勒影响下,传统方法适应性下降,所提改进方法有9 dB的性能提高。通过对湖上实验数据的处理也验证了所提方法的有效性。     

Broadband PVDF membrane hydrophone for comparisons of hydrophone calibration methods up to 140 MHz

A PVDF membrane hydrophone has been constructed in particular for comparisons of broadband ultrasound hydrophone calibration methods and of the results obtained by different laboratories. Intercomparisons have to accompany the efforts currently undertaken to enhance the calibration frequency ranges and to implement the extension from the determination of amplitude-only to complex-valued calibration data. It can be expected that such hydrophone data will be used much more frequently in the future for exposure measurements on medical ultrasound equipment, in particular for the detection of nonlinearly distorted waveforms. The hydrophone design chosen has a foil thickness of 9 microm and an electrode diameter of 210 microm. A broadband differential preamplifier (-3 dB roll-off frequency: 95 MHz) is integrated to achieve a high signal-to-noise ratio over a broad frequency range (e.g., 26 dB-30 dB in the range 50 MHz to 140 MHz for measurements of nonlinearly distorted pulses). The hydrophone response was characterized by means of a primary interferometric calibration technique, by substitution calibration using time-delay spectrometry, and by complex broadband pulse calibration using nonlinear sound propagation. The results show a flat frequency response up to 40 MHz (maximum variations below +/-0.6 dB) and a thickness mode resonance at about 105 MHz. They indicate a useable bandwidth up to 140 MHz. The effective diameter as derived from directional response measurements is 240 microm at frequencies beyond 15 MHz.     

微弱裂纹信号的稀疏编码提取

针对重大技术装备中关键基础部件早期裂纹信号提取困难这一问题,提出一种基于独立分量分析（ICA）的稀疏编码收缩（SCS）去噪方法,即采用泛化高斯模型（GGM）在ICA空间中估计信号独立系数的概率密度函数（PDF）,并利用最大后验（MAP）估计方法进行非线性去噪的微弱信号提取方法。通过对不同信噪比的含噪微弱裂纹信号的提取研究,结果表明,此方法能提取出输入信噪比低于-27dB的微弱信号,且波形与频谱均能较好的和原信号保持一致。同时,其去噪效果远远好于小波降噪方法,是一种较好的微弱信号提取方法。