一种改进的基于LC-GSC的主瓣干扰抑制方法

针对线性约束广义旁瓣相消器(LC-GSC)存在主瓣干扰时天线自适应方向图会出现主瓣波束畸变及副瓣电平升高的问题,给出了一种通过阻塞矩阵对数据进行预处理的主瓣干扰抑制方法,对线性约束广义旁瓣相消器进行了改进,先利用阻塞矩阵预处理实现主瓣干扰抑制,再通过线性约束广义旁瓣相消器进行波束形成,有效地解决了波束主瓣变形及旁瓣电平升高的问题。仿真分析验证了改进方法的有效性。     

基于投影对消处理技术的稳健自适应波束形成

针对传统自适应波束形成算法中目标波达方向(Direction of Arrival,DOA)估计不准确引起的波束形成性能下降问题,提出了一种采用投影对消矩阵的稳健自适应波束形成算法.首先,寻找与估计波达方向有最大相关性的特征矢量作为目标信号特征矢量,然后构建对消矩阵消除协方差矩阵中的信号分量,最后通过增加零点约束实现干扰抑制.与传统对角加载类稳健波束形成算法相比,所提算法不受对角加载因子的影响,且在信干噪比较大时仍然具有良好的抗干扰性能.仿真对比实验验证了所提算法的有效性.     

线性干扰参数约束的稳健LSMI波束形成算法

 针对稳健的加载样本矩阵求逆(LSMI)波束形成算法,给出了一种新的求解方法,获得了加载电平的准确计算公式,而且得出最优加载量为负值,且与约束参数的选取无关.为了改善LSMI波束形成算法的抗干扰性能,提出利用线性干扰参数约束(LJC)来实现,其中对LJC-LSMI波束形成算法进行了建模和求解,得到了最优加权矢量的表达式,并给出了具体的求解方法.仿真分析验证了算法的正确性和有效性,结果表明LJC-LSMI相对于LSMI具有较强的干扰抑制能力,相对于线性约束最小功率(LCMP)波束形成算法具有稳健的波束指向性能.     

主瓣干扰下自适应方向图保形方法的研究

当存在主瓣干扰时，自适应天线方向图会出现副瓣电平升高及主波束变形的严重问题。本文提出了基于阻塞矩阵预处理的自适应波束保形方法和基于特征投影预处理的自适应波束保形方法，这两种方法在抑制干扰的同时，有效地解决了上述的波束畸变问题。仿真结果证明了这两种方法的有效性。     

基于干扰位置预测的稳健波束形成方法

高速平台雷达阵列进行自适应波束形成时,干扰方向的快速变化和波束指向误差会导致输出信干噪比的急剧下降.针对上述问题,提出了一种基于干扰位置预测的稳健波束形成方法.该方法首先定义了归一化空间频率,对权值应用时期的干扰位置进行预测,给出零陷范围;然后采用矩阵加权的方式对零陷范围进行低增益约束并保持主瓣区域增益,从而实现干扰抑制,提高波束形成对指向误差的稳健性.仿真实验证明了所提方法的有效性.     

一种基于线性约束的自适应方向图控制方法

提出了一种基于线性约束最小方差波束形成（LCMV）的自适应方向图控制方法。该方法通过在原有线性约束基础上构造新的线性约束,然后根据新组成的线性约束进行LCMV自适应波束形成,所得到的自适应方向图在固定零点方向和干扰方向形成零陷的同时保留了期望静态方向图的副瓣电平特性,从而能够减小快变干扰的影响,并且计算十分简便。计算机仿真证明了本文方法的有效性。     

一种新的波束形成零陷展宽算法

针对自适应波束形成器在干扰位置出现扰动时的输出性能下降问题,该文提出一种新的零陷展宽算法。该算法基于投影变换与对角加载技术的结合,首先利用投影变换技术对阵列接收数据进行预处理,结合对角加载技术,以此构造出一个新的协方差矩阵替代原来的协方差矩阵,再利用自适应波束形成技术得到零陷展宽后的波束图。仿真结果表明,该方法能有效展宽波束零陷宽度,加深零陷深度,达到抑制位置出现扰动的强干扰信号目的。该算法易于求解,对参数的选取具有较强稳健性,在低快拍条件下,依然能有效地工作,增强了自适应波束形成器稳定性。     

基于协方差矩阵双层重构的稳健自适应单脉冲测角

常规自适应单脉冲方法在主瓣干扰下会引起自适应波束形成性能恶化并导致其单脉冲比曲线严重失真,影响被动雷达的测角精度与跟踪性能。针对此问题,提出了一种适用于平面阵的基于协方差矩阵双层重构的稳健自适应单脉冲测角方法。首先,利用Capon功率谱通过稀疏重构法初步估计出干扰加噪声协方差矩阵,通过干扰导向矢量估计完成对协方差矩阵的优化校正以提高自适应波束形成性能;然后,基于线性约束最小方差（Linearly Constrained Minimum Variance,LCMV）准则对方位角和俯仰角进行联合线性约束以避免单脉冲比曲线在主瓣干扰下严重失真;最后,根据自适应单脉冲比值求出目标与波束指向之间的偏转角以实现目标测角。与常规方法相比,所提方法在干扰抑制能力与测角精度上都有显著提升。     

基于特征值斜投影的主瓣干扰抑制方法

主瓣干扰将导致传统自适应波束形成算法的主瓣畸变、峰值偏移、旁瓣电平抬升,致使相控阵系统抗干扰性能严重恶化.另外,当接收快拍中存在目标信号时,会导致自适应波束形成在目标信号方向生成零陷,降低接收目标信号增益.针对这些问题,本文提出一种基于特征值斜投影的主瓣干扰抑制方法.首先通过构建特征值斜投影预处理矩阵滤除主瓣干扰,然后...     

阻塞矩阵抗干扰方法性能分析

阻塞矩阵抗干扰方法在阵列抗干扰方面已有较多研究,该方法利用阻塞预处理将主瓣干扰信号去除,之后自适应波束形成处理实现副瓣干扰抑制和主瓣保形,但其抗干扰性能尚缺乏详细分析。文中推导了算法的实现原理,引入抗干扰等效权矢量,并采用阵列输出信干噪比增益指标、抗干扰方向图等对抗干扰性能进行分析,仿真结果表明,当存在主瓣干扰时,该方法会带来副瓣电平增高、主波束变形及偏移等问题,同时还会引起阵列自由度损失,导致抗干扰性能变差。      

基于BMP及CMR的抗主瓣干扰算法研究

瓣干扰算法。通过分析阻塞矩阵预处理后数据特征值的变化情况,修正预处理导致的过处理现象,从而重构协方差矩阵,该算法适用于阻塞矩阵预处理导致的自由度损失的情况,能够解决由于预处理导致的主瓣波峰偏移等失真问题,同时算法复杂度较低。该算法最大的优点是当采样快拍包含目标信号时,其抗干扰性能较好,快拍敏感度相比常规的波束保形方法更低,经实测数据验证,结果显示出该算法的优越性。     

频率不变约束的角加载稳健宽带波束形成算法

应用角加载技术能够提高波束形成算法稳健性,但是角加载量确定却是一个难解决问题。文中提出了一种基于频率不变约束的可变角加载最优稳健波束形成算法(Frequency Invariance Constraints-Variable Diagonal Loading,FIC-VDL)。该算法基于宽带波束形成的时域模型,根据多频点约束下导向矢量的不确定范围,利用频率不变约束因子将多频点变为参考频点约束来求解最优角加载量,并推导出真实的导向矢量。该方法能够改善宽带波束形成器在期望方向的频率不变特性,同时降低系统计算复杂度。计算机仿真结果验证了所提算法的稳健性。     

一种波束形成中的自适应对角加载方法

在自适应波束形成中，由于采样快拍数有限，导致协方差矩阵的估计误差，由此得到的自适应波束旁瓣很高。对角加载方法是一种改善波束性能的有效方法。文章介绍了对角加载的原理，给出了一种对角加载值的确定方法和仿真效果。该方法能根据采样数据自适应调整对角加载的数值，实现容易，能得到很好的旁瓣特性。     

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

Adaptive beamforming methods are known to degrade if some of underlying assumptions on the environment, sources, or sensor array become violated. In particular, if the desired signal is present in training snapshots, the adaptive array performance may be quite sensitive even to slight mismatches between the presumed and actual signal steering vectors (spatial signatures). Such mismatches can occur as a result of environmental nonstationarities, look direction errors, imperfect array calibration, distorted antenna shape, as well as distortions caused by medium inhomogeneities, near-far mismatch, source spreading, and local scattering. The similar type of performance degradation can occur when the signal steering vector is known exactly but the training sample size is small. In this paper, we develop a new approach to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch. Our approach is based on the optimization of worst-case performance. It turns out that the natural formulation of this adaptive beamforming problem involves minimization of a quadratic function subject to infinitely many nonconvex quadratic constraints. We show that this (originally intractable) problem can be reformulated in a convex form as the so-called second-order cone (SOC) program and solved efficiently (in polynomial time) using the well-established interior point method. It is also shown that the proposed technique can be interpreted in terms of diagonal loading where the optimal value of the diagonal loading factor is computed based on the known level of uncertainty of the signal steering vector. Computer simulations with several frequently encountered types of signal steering vector mismatches show better performance of our robust beamformer as compared with existing adaptive beamforming algorithms.     

高精度多功能自适应相控阵天线的研究

从发掘相控阵天线潜力使其具有高精度、抗干扰和多功能等角度出发,对下列课题进行了研究：适当随机相位量化优化波束指向的算法;适当相位加权和振幅加权波瓣置零实数算法;适当相位加权和振幅加权的ＤＢＦ实数算法;随机对角线加载算法对自适应算法的影响;新的线性调频信号检测和估计方法;非对称波瓣算法。以上算法均采用了适当改变技术（ＡＣＴ）。计算机模拟结果证明,这些算法是行之有效的。     

Two-Dimensional Adaptive Array Beamforming With Multiple Beam Constraints Using a Generalized Sidelobe Canceller

This paper deals with the problem of two-dimensional (2-D) adaptive array beamforming with multiple beam constraints (MBC) using a generalized sidelobe canceller (GSC). We present a method for the construction of signal blocking matrix required by the 2-D GSC. The resulting 2-D adaptive beamformer can provide almost the same performance as conventional 2-D adaptive beamformers based on a linearly constrained minimum variance (LCMV) criterion. The effectiveness of the proposed GSC is that the construction of the required signal blocking matrix requires only the computation of a few entries from analytical formulas. In comparison with conventional methods, the proposed technique gets rid of the computational complexity due to the eigendecomposition required for finding the 2-D signal blocking matrix. For dealing with the performance degradation due to coherent interference, we present a 2-D weighted spatial smoothing scheme to effectively alleviate the coherent jamming effect. Several simulation examples are provided for illustration and comparison.     

Robust Adaptive Beamforming Under Quadratic Constraint with Recursive Method Implementation

When adaptive arrays are applied to practical problems, the performances of the conventional adaptive beamforming algorithms are known to degrade substantially in the presence of even slight mismatches between the actual and presumed array responses to the desired signal. Similar types of performance degradation can occur because of data nonstationarity and small training sample size, when the signal steering vector is known exactly. In this paper, to account for mismatches, we propose robust adaptive beamforming algorithm for implementing a quadratic inequality constraint with recursive method updating, which is based on explicit modeling of uncertainties in the desired signal array response and data covariance matrix. We show that the proposed algorithm belongs to the class of diagonal loading approaches, but diagonal loading terms can be precisely calculated based on the given level of uncertainties in the signal array response and data covariance matrix. The variable diagonal loading term is added at each recursive step, which leads to a simpler closed-form algorithm. Our proposed robust recursive algorithm improves the overall robustness against the signal steering vector mismatches and small training sample size, enhances the array system performance under random perturbations in sensor parameters and makes the mean output array SINR consistently close to the optimal one. Moreover, the proposed robust adaptive beamforming can be efficiently computed at a low complexity cost compared with the conventional adaptive beamforming algorithms. Computer simulation results demonstrate excellent performance of our proposed algorithm as compared with the existing adaptive beamforming algorithms.