主动声纳直达波干扰抑制的盲分离算法

针对舰艇编队作战中主动声纳之间存在的强直达波干扰,提出了一种基于信号统计二阶矩的直达波干扰抑制算法,实现了强干扰背景下的微弱目标回波检测。这种方法将盲分离理论和匹配相关技术相结合,首先对接收数据进行直达波干扰抑制,再利用已知发射信号副本进行匹配相关,最后提取目标回波信号。相比其它强干扰抑制算法,特别是高阶累计量法,该算法具有计算复杂度低的优点。通过数值仿真实验表明：该算法能够对直达波干扰进行有效抑制,对目标回波的检测性能优于直接匹配相关方法。     

基于零陷展宽的双基地声纳直达波抑制算法

双基地声纳系统中存在目标信号与直达波干扰混叠且两者高相关的情况,常规的自适应抵消法因此失效。在双基地声纳系统配置已知的前提下,提出一种基于零陷展宽技术的多约束最小方差直达波抑制算法。该方法通过施加线性约束对特定方向的干扰进行抑制,并针对直达波干扰方位存在扰动时,多约束最小方差算法性能急剧下降的现象运用零陷展宽的方法对算法加以改进。基于零陷展宽的多约束最小方差算法直观、快捷。仿真及实验数据处理的结果表明,在直达波干扰方位大致可知的情况下,该算法能够对直达波进行有效抑制,且对直达波的方位估计误差具有稳健性。     

一种自适应的主动声呐直达波干扰抑制算法

为了克服主动声呐编队作战条件下的直达波干扰,达到检测微弱目标回波信号的目的．提出了一种基于频域分块自适应滤波算法的直达波抑制方法。这种方法将自适应滤波理论和匹配相关技术相结合,首先对接收数据做频域分块自适应滤波,再利用已知发射信号副本进行匹配相关,最后提取目标回波信号。其中,频域分块自适应滤波算法相比基本最小均方算法,计算复杂度降低,收敛速度快,基本保证了主动声呐每个探测周期内的直达波抑制和目标回波的提取。通过数值仿真实验表明：在强直达波干扰存在条件下,该算法对目标回波的提取在精度和鲁棒性等方面均优于以往的直接匹配相关方法。     

采用包络检波去除SISAR直达波干扰的新方法

为了去除直达波干扰，从强的直达波干扰背景中有效提取SISAR侧影成像的目标全息信号，提出了对接收的含有目标全息信号和强直达波的混合信号直接进行包络检波，然后通过对检波后的输出进行时域的正交分解，恢复目标的全息信号的新方法．仿真结果验证了理论分析的正确性。     

改进的二维滤波技术在浅层地声探测中的应用

利用声波反射原理探测地下浅层物体是一种较为有效的探测方法。经过多年的探索，我们已形成了以爆炸和锤击等有较高分辨率的瞬态信号作为声源，采用传感器直线阵接收，后续结合阵列信号处理技术完成目标信号的提取和成像处理的探测方案。该声探测系统在实测中，地表直达波对物体反射波的强干扰是限制探测灵敏度的主要原因之一。因此，抑制强干扰，提取有效信号，是实现目标正确探测和定位的先决条件。由于探测深度较浅，反射波和直达波混迭在一起，在频率域或时间域很难将强干扰和信号分开。于是就提出了利用直达波和反射波视速度的差异对频…     

四分之一波长间距阵抗拖船干扰研究

为改善拖曳线列阵声呐的尾向探测能力,降低拖船噪声对半波长间距阵尾向探测性能的制约,本文关注四分之一波长间距阵对连续波信号和带限噪声的响应。研究表明,四分之一波长间距阵具有非对称的端向指向性,与半波长间距阵相比有约20 d B的空间抑制能力,能有效抑制拖船辐射噪声干扰。本文还提出用零陷权组合传感器构成四分之一波长间距阵,理论上其抗拖船噪声干扰的效果比四分之一波长间距阵更好。     

无源探测雷达系统中非平稳直达波抑制方法研究

在基于非合作照射源的无源雷达系统中,对直达波的抑制是一项关键技术。非合作照射源发射的信号多为非平稳信号,传统方法最小均方算法收敛速度慢,不能适应上述信号的变化,降低系统性能。提出改进的归一化LMS算法,利用变步长技术,改善算法的收敛速度,进而提高了非平稳直达波和杂波的抑制性能。实测数据的处理和实际系统中的应用均验证了该算法的有效性。     

有向阵元圆形阵列声纳波束形成原理及实现

有向阵元阵列接收具有区域指定性好和灵敏度高的优点而被广泛应用于雷达、水声信号目标探测。探讨了基于有向阵元圆阵的波束形成原理并设计出基于FPGA的自适应数字波束形成（ADBF）模块,仿真结果表明有向阵元形成的波束图较全向阵波束图有明显改善,LMS自适应算法对干扰能有效抑制,从而提高了系统输出信号干扰噪声比（SINR）。     

锁定放大技术在参量接收阵中的应用

为抑制泵波影响,提取参量接收阵中的微弱差频信号,根据微弱信号探测原理,设计了一个基于锁定放大技术的参量接收阵系统。简要介绍了参量接收阵原理,详细描述了锁定放大技术,以及所设计的参量接收阵系统的工作过程,给出泵波比差频高130 dB时的仿真数据。结果表明,采用锁定放大技术后的参量接收阵系统可对接收的差频信号优化约5 dB。     

一种物体前向散射声场异常的增强方法

0引言当物体穿过双基地声纳收发连线时,散射信号与直达信号时频空域上均发生重叠,此时双基地声纳传统的检测方法失效。但是,由于物体的前向散射作用,散射信号与直达信号产生干涉,使得接收声场会产生异常变化,该现象可作为物体入侵的标识。前向散射探测面临的问题是,随着接收距离的增大,直达波的干扰变强,前向散射引起接收声场     

Phase-only adaptive nulling with neural networks for antenna array synthesis

A new approach to adaptive phase-only nulling with phased arrays is described. An efficient method is presented to synthesise directive beam and multi-beam patterns and create adaptive nulls in interference direction. The proposed method is based on iterative minimisation of a function that incorporates constraints imposed in each direction with respect to excitation phases and neural network technique. Various results are presented to show the advantages and limitations of this approach. The back-propagation algorithm proves to be better than previous phase-only adaptive algorithms. To verify the performances of the proposed technique, an eight-element array has been realised and tested for various types of beam configurations.     

Enhanced NLMS adaptive array via DOA detection

In various adaptive array applications, the desired-user signal arrives from only a relatively small number of directions. The paper proposes an NLMS-based adaptive algorithm that incorporates a direction of arrival (DOA) detection criterion. The criterion stems from Akaike's information criterion and Donoho's thresholding principle. Within `low-dimensional' DOA applications, the inclusion of the DOA detection criterion leads to a reduction in the number of NLMS adapted parameters. The result is significantly improved convergence and tracking speeds, as well as improved nulling of multi-user interference signals. Simulations demonstrate the favourable performance of the proposed NLMS adaptive-array system     

Optoelectronic implementation of a 256-channel sonar adaptive-array processor

We present an optoelectronic implementation of an adaptive-array processor that is capable of performing beam forming and jammer nulling in signals of wide fractional bandwidth that are detected by an array of arbitrary topology. The optical system makes use of a two-dimensional scrolling spatial light modulator to represent an array of input signals in 256 tapped delay lines, two acousto-optic modulators for modulating the feedback error signal, and a photorefractive crystal for representing the adaptive weights as holographic gratings. Gradient-descent learning is used to dynamically adapt the holographic weights to optimally form multiple beams and to null out multiple interference sources, either in the near field or in the far field. Space-integration followed by differential heterodyne detection is used for generating the system's output. The processor is analyzed to show the effects of exponential weight decay on the optimum solution and on the convergence conditions. Several experimental results are presented that validate the system's capacity for broadband beam forming and jammer nulling for linear and circular arrays.     

Vector Field Smoothing for DOA Estimation of Coherent Underwater Acoustic Signals in Presence of a Reflecting Boundary

A new vector field smoothing algorithm for direction-of-arrival (DOA) estimation of multiple coherent, underwater acoustic signals is proposed based on the array with vector hydrophones, which is located at or near a reflecting boundary. The performance of the proposed algorithm is examined in two practical applications: hull-mounted and seabed array. The advantage of the vector field smoothing scheme is no reduction in the overall array's spatial aperture.     

一种最佳空间滤波器在圆柱型基阵上的实现

根据最佳空间滤波器的数学表述,在圆柱型基阵上实现了最佳空间滤波器。研究了目标附近数个干扰源存在情况下弱信号检测及干扰的抑制效果。表明在圆柱型基阵上最佳空间滤波器能够有效抑制多个干扰、完成弱信号检测。设计的最佳空间滤波器实现方法可以方便地在圆柱型基阵上实现。     

双微阵列语音增强算法在说话人识别中的应用

针对复杂噪声环境下识别性能显著降低的问题,提出一种用于说话人识别系统前端的双微阵列语音增强算法。该算法采用的是相干滤波和频域宽带最小方差无畸变响应波束形成器后置结合改进的维纳滤波器。其基本原理是首先求出双微麦克风阵列信号中两个相邻通道间的相干函数,再利用通道间信号的相干性来进行初始噪声抑制。其次,通过一个频域宽带最小方差无畸变响应(Minimum Variance Distortionless Response,MVDR)波束形成器保留目标声源方向的信号并抑制其他方向的信号干扰,再通过改进的维纳滤波器去除噪声残留提升语音质量。最后,使用梅尔频率倒谱系数(Mel Frequency Cepstral Coefficients,MFCC)和伽马通滤波器组频率倒谱系数(Gammatone Filter-bank Frequency Cepstral Coefficients,GFCC)对增强后的语音信号做特征参数提取并进行说话人识别。仿真过程采用声学人工头模拟双耳采集数据,实验结果表明,该语音增强算法在复杂噪声环境下能够获得较好的增强效果,能有效提升说话人识别系统的识别率。     

Dynamic null steering in an ultrawideband time-steered array antenna

We develop a method for forming squint-free wideband nulls in the antenna pattern of an ultrawideband array antenna. The technique uses an optical dispersive-prism beam former to provide time-delayed microwave signals to each antenna element for forming a squint-free main beam. The amplitude-modulated optical carrier is propagated through a set of optical links. Each link feeds an array element and includes an amount of dispersion proportional to element position. Tuning the wavelength of the optical carrier controls the microwave signal's arrival-time delay gradient across the array. A dispersive-prism tapped delay-line microwave filter is used to frequency shape a nulling signal. The wideband nulls do not significantly distort the main beam and are steered independently of the main beam. The technique is applied to sidelobe nulling for a transmitter and for jammer suppression for a receiver array.     

基于形态学算子的睫毛干扰抑制算法

针对虹膜识别中的睫毛干扰抑制问题,本文提出了一种基于形态学算子的睫毛干扰抑制算法.该算法将虹膜图像中的睫毛对象看作是背景图像中存在的随机的,不规则的细微裂缝,通过膨胀算子对这些裂缝进行像素填补,实现了对睫毛干扰的有效抑制.与常见的高斯滤波法相比,所提算法具有更强的睫毛干扰抑制能力.通过CASIA虹膜库的仿真实验表明,所提算法比高斯滤波法消除的睫毛像素点要多40%,可以使Daugman和Wildes定位算法的定位精度分别提高1.7%和2%,定位时间分别减少27.9%和24.2%.     

Neural network method for direction of arrival estimation with uniform cylindrical microstrip patch array

In this study, a new neural network algorithm is proposed for real-time multiple source tracking problem with cylindrical patch antenna array based on a previously reported Modified Neural Multiple Source Tracking (MN-MUST) algorithm. The proposed algorithm, namely cylindrical microstrip patch array modified neural multiple source tracking (CMN-MUST) algorithm implements MN-MUST algorithm on a cylindrical microstrip patch array structure. CMN-MUST algorithm uses the advantage of directive pattern of microstrip patch elements by considering only a part of array elements for a chosen sector. This reduces neural network sizes and also improves the spatial filtering performance. The proposed algorithm improves MN-MUST algorithm in the sense of accuracy and speed while covering the full azimuth range.