对相控阵雷达自适应旁瓣对消干扰技术研究

自适应旁瓣对消雷达系统能够有效对抗来自副瓣方向的有源干扰,在分析相控阵雷达自适应旁瓣对消工作原理基础上,基于设计的辅助天线配置方案,针对干扰源相对雷达角度变化以及雷达天线方向图差异,对自适应旁瓣对消雷达系统的对消性能进行了系统全面仿真。仿真实验结果表明,多个单一极化干扰源和单个极化干扰源对自适应旁瓣对消雷达系统分别干扰时,闪烁干扰和极化干扰方法都存在干扰不理想的情况,因此,建议对自适应旁瓣对消雷达系统实施旁瓣干扰时,采用多点干扰源闪烁干扰和极化干扰复合的干扰策略。     

北斗导航接收机旁瓣对消技术研究

北斗导航信号数字化处理技术的研究和发展越来越受到人们的关注,自适应天线旁瓣对消技术在北斗导航接收机中得到了广泛应用。分析了自适应天线旁瓣对消的基本原理,给出了在相对带宽较宽的干扰下按照最小均方(LMS)准则求解最优权值的计算过程以及基于Cholesky分解求取干扰信号自相关矩阵逆阵的方法。最后通过MATLAB对所设计的自适应天线旁瓣对消系统进行仿真分析,其结果表明自适应旁瓣对消技术可有效对抗宽带干扰。     

改进的基于旁瓣对消的单脉冲测角算法

研究了基于自适应广义旁瓣对消技术的单脉冲角度跟踪算法。在自适应广义旁瓣对消器(G enera l s ide lobecance ller,G SC)结构下,当存在指向误差的时候,阻塞矩阵不能完全阻塞期望信号,导致辅助支路上产生期望信号泄露,从而使得单脉冲角度跟踪性能下降。为了解决此问题,提出了一种基于辅助支路子空间投影的算法,该算法利用了期望信号空间和干扰空间正交的特点,减少了泄露的期望信号对波束形成性能的影响,从而保证了单脉冲角度跟踪的性能。理论分析和仿真结果表明了该算法的有效性和优越性。     

抗交串自适应噪声对消系统的算法实现

针对一般的自适应噪声对消系统性能上存在的不足,引入了抗交串自适应噪声对消系统.抗交串自适应噪声对消系统在形式上由两个典型的自适应噪声对消模块串接而成.抗交串自适应噪声对消系统无须预先知道信号和噪声的特征,却能够相当好地抑制噪声的影响,又使有用信号不产生畸变.该文叙述了该系统的算法实现.计算机仿真结果表明,在强噪声环境背景下,该算法将功率信噪比提高了50db左右,而且运算速度快.该算法对某些特定采样信号的分析和处理有重要意义.     

神经网络自适应噪声对消的研究

基于神经网络中自适应线性单元(ADALINE),结合传统自适应噪声对消原理,提出了一种基于ADALINE的改进型自适应噪声对消器。经仿真和实例证明,具有很强的噪声滤除能力和鲁棒性。     

基于辨识新算法的电子对抗系统干扰对消

收发同时的电子对抗系统常存在隔离问题,采用自适应滤波器对干扰耦合通路进行辨识,消除接收端耦合干扰,能够有效实现收发隔离.考虑到实际侦察接收机接收的雷达信号、接收机内部引入的噪声信号、发射机和接收机微波放大部分的非线性,因素严重影响自适应滤波器的性能.针对上述情况,给出一种平滑梯度估计的变步长最小均方(least mean square,LMS)算法.仿真结果表明,改进算法同传统变步长LMS算法相比具有相近的收敛速度,但在对抗接收机复杂信号环境上具有显著的优越性能.     

基于自适应滤波原理的扩频窄带干扰对消技术

本文在介绍了扩频通信的基本原理的基础上,重点研究了用自适应滤波原理对扩频信号中的窄带干扰进行消除的方法,并建立模型进行了仿真分析。结果表明,用两个自适应滤波器组成的双环噪声消除器对扩频信号中的窄带干扰可以起到非常理想的抑制作用。     

基于量子神经网络的无线电引信干扰对消

为了提高无线电引信的抗干扰性,采用量子神经网络构建非线性滤波器,自适应抵消回波信号中包含的干扰噪声。通过自适应干扰对消系统仿真,实现了对目标反射信号的最优恢复,获得了理想的降噪效果。     

残留频差对自适应阵列天线的影响

自适应阵列天线可以通过数字下变频实现信号正交化,把中频数字信号转换到零中频,然后进行加权求和.分析了变频过程中因没有进行载波同步所导致的残留频差对自适应阵列天线算法的影响.通过详细的理论分析表明,只要上、下变频采用相同本振,残留频差对算法并没有影响,即使对带通采样系统,该结论同样成立.对频谱、阵列增益的仿真证明了理论分析的正确性.     

一种精确控制旁瓣的自适应波束形成算法

提出了一种精确控制旁瓣和抑制干扰的自适应波束形成算法。它是通常的最小方差无畸变（MVDR）波束形成算法的改进形式，使阵列输出信号功率最小的同时，保持目标信号方向的无失真响应，并且严格保证旁瓣低于某一给定值，抑制干扰。在仿真过程中，充分应用了二阶锥规划（second—order cone programming）算法，并与MVDR波束形成算法进行比较，验证了方法的正确性，同时研究了该算法的稳健性。     

Hybrid probabilistic adaptation mode controller for generalized sidelobe cancellers applied to multi-microphone speech enhancement

In this paper, we propose a new adaptation mode controller (AMC) for a generalized sidelobe canceller (GSC)-based speech enhancement system. Here, a likelihood ratio for target speech presence was first estimated and then utilized to estimate both the local target speech presence probability (SPP) and global SPP. Next, the estimated SPPs were applied to the design of an AMC that controlled the parameters of adaptive filters for an adaptive blocking matrix (ABM) and noise canceller (NC). In particular, the combination of local and global SPPs was applied to the AMC in the ABM, whereas only global SPPs were used for the NC. Finally, a multiple-microphone speech enhancement system was constructed on the basis of a GSC having the proposed AMC. The performance of the speech enhancement system was subsequently evaluated in terms of the perceptual evaluation of speech quality (PESQ) and the cepstral distortion (CD) for car noise conditions. It was shown from this evaluation that a speech enhancement system using the proposed AMC method provided better performance than conventional AMC methods using power ratios between the target and non-target directional signals, the inter-channel normalized cross-correlation, and the local SPPs only.     

一种广义旁瓣抵消器结构的语音增强改进算法

当广义旁瓣抵消器（Generalized sidelobe canceller,GSC）结构的语音增强算法对语音信号的入射方向角估计不准确时,阻塞矩阵（Blocking matrix,BM）不能完全阻塞目标语音,使得部分语音通过阻塞矩阵,在后期多输入抵消器（Multiple-input canceller,MC）模块中和参考信号相抵消,造成目标语音的损失。针对广义旁瓣抵消器因信号到达方向（Direction of arrival,DOA）估计误差而导致语音泄漏的问题,本文提出了一种麦克风阵列语音增强的优化算法,先对经过时延补偿的信号进行频谱调整,再利用MC模块输出与BM模块输出存在相关性的特点,对阻塞矩阵进行自适应调整,使方向估计参数更趋近于真实目标语音方向,以减少阻塞矩阵中目标语音的泄漏。仿真结果表明,该算法可以有效减少阻塞矩阵中目标语音的泄漏、增强系统的鲁棒性以及提高语音增强效果。     

磁异信号自适应检测算法

针对在分形噪声1/fα(0≤α2)中检测磁异信号存在的问题,提出了一种自适应噪声抵消器与自适应AR白化滤波器相结合的磁异信号正交基函数(OBF)检测算法——改进的OBF检测算法。由于固定AR白化滤波器对分形噪声1/fα的白化效果不佳,影响了OBF检测算法的性能,因此采用自适应噪声抵消器对被检测信号进行预处理以提高其信噪比,再利用自适应AR白化滤波器对预处理信号进行白化滤波,以实现OBF检测算法的最优化。理论仿真结果表明:当α值接近于0时,改进的OBF检测算法的处理增益略高于未经白化的OBF检测算法;当α值接近于2时,改进的OBF检测算法的处理增益略高于基于AR白化滤波器的OBF检测算法;当α值约等于0.8时,改进的OBF检测算法的处理增益高于其他两种算法7 dB,实验结果表明改进的OBF检测算法可以检测更微弱的磁异信号。     

Speech enhancement with a GSC-like structure employing sparse coding

Speech comnmnication is often influenced by various types of interfering signals. To improve the quality of the desired signal, a generalized sidelobe canceller （GSC）, which uses a reference signal to estimate the interfering signal, is attracting attention of researchers. However, the interference suppression of GSC is limited since a little residual desired signal leaks into the reference signal. To overcome this problem, we use sparse coding to suppress the residual desired signal while preserving the reference signal. Sparse coding with the learned dictionary is usually used to reconstruct the desired signal. As the training samples of a desired signal for dictionary learning are not observable in the real environment, the reconstructed desired signal may contain a lot of residual interfering signal. In contrast, the training samples of the interfering signal during the absence of the desired signal for interferer dictionary learning can be achieved through voice activity detection （VAD）. Since the reference signal of an interfering signal is coherent to the interferer dictionary, it can be well restructured by sparse coding, while the residual desired signal will be removed. The performance of GSC will be improved since the estimate of the interfering signal with the proposed reference signal is more accurate than ever. Simulation and experiments on a real acoustic environment show that our proposed method is effective in suppressing interfering signals.     

音响系统回波抵消研究

针对音响系统在室内产生的回波干扰,采用基于频域回波抵消算法,结合DSP芯片TMS320VC5416硬件的处理方法,设计了RS232串口通讯的人机界面控制程序,从而有效地消除了干扰噪音。该方法可用于多种音频设备、会议系统,以抵消回波产生的干扰。     

基于改进的NLMP的自适应脉冲噪声对消器

在信号传输系统中,存在自适应算法不能处理的α-稳定脉冲噪声,在算法中将步长更新与系统输出误差e(n)的lp范数联系起来,利用系统的输出误差e(n)来确定自适应系统的步长,提出了一种适用于α-稳定脉冲噪声环境下的改进的NLMP自适应对消算法(MNLMP)。MNLMP很好地解决了NLMP算法收敛速度与稳态误差不能兼顾的缺点。通过计算机仿真,结果显示MNLMP比LMP、NLMP有更好的对消性能。同时,仿真结果显示在不同输入信噪比的情况下,MNLMP算法的输出信噪比其它两种算法有了明显的提高。     

Blind Capon-like adaptive ST-BC MIMO-CDMA receiver based on constant modulus criterion

In this paper, we present a new Capon-like blind receiver based on linearly constrained constant modulus (LCCM) criterion for the multiple-input multiple-output (MIMO) antennas system along with space–time block code (ST-BC) using direct-sequence code division multiple access (CDMA) modulation technique. A time-varying channel model with generalized sidelobe canceller (GSC) associated with the recursive least squares (RLS) algorithm is implemented to reduce the complexity of receiver design. In our derived algorithm, the parameter of constant modulus, α, relating to the desired user power is updated adaptively via stochastic gradient algorithm to track user?s amplitude variation. Also we prove theoretically that in the two-branch filter bank receiver design the weight vector of one branch can be updated simply using the other one, which has been obtained with our proposed CM-GSC-RLS algorithm, with simple pre-calculated transform. Hence computation complexity of the proposed adaptive blind receiver can be further reduced significantly. Via intense simulations it reveals that our proposed scheme has robust performance against the user?s acquisition inaccuracies comparing with current available algorithms.