基于特征空间的线性约束最小方差波束形成器

该文把线性约束和特征空间技术相结合,提出了基于特征空间的线性约束最小方差波束形成器(ELCMVB),该波束形成器是把线性约束最小方差波束形成器(LCMVB)的预定约束方向导向矢量向信号子空间投影,再结合线性约束用LCMVB来得到权矢量。经分析表明,ELCMVB的性能优于GEIB的性能。与GEIB相比,ELCMVB不用计算修改的信号子空间,避免了因计算修改信号子空间而容易造成的计算不稳定性,且其波束形成性能基本上不受零点约束位置的影响。最后,给出了计算机仿真结果,并证实了ELCMVB的优越性。     

一种冲击噪声环境下的最优波束形成算法

针对冲击噪声（包括所有对称α稳定分布噪声）环境下一般未知噪声统计特性,提出了一种最小几何功率无失真响应波束形成算法。该算法利用求取有限对数矩时无需噪声统计特性的特点,用对数矩代替二阶矩在约束期望信号增益为1的条件下使快拍信号的几何功率最小,最终使输出信号能达到更高的几何信干噪比。并通过一种新的迭代的方法得到最优权向量。仿真实验证明了该算法的有效性。     

相位响应固定幅度响应约束的稳健波束形成方法

传统的幅度约束波束形成器是一个非凸问题,需将原始模型化为线性规划进行间接求解。该文针对均匀线阵提出一种相位响应固定幅度响应约束(PFMC)的稳健波束形成方法。利用权矢量逆序列对应的传递函数与阵列响应函数只差一个相位因子这一性质,将阵列响应的相位设置为固定的线性相位,仅对阵列响应的实数幅度进行约束,从而得到一个凸的代价函数,最优权矢量可以利用内点法求出。同时考虑到协方差矩阵误差,利用最坏(WC)情况性能最优原理提出PFMC-WC算法改善PFMC的性能。与传统幅度约束波束形成器相比,减少了约束个数并省掉了恢复权矢量过程,从而降低了计算量。此外,由于相位响应得到保证,该文算法相对于传统算法具有更好的性能。仿真实验验证了该文算法的有效性。     

基于特征空间的相干干扰抑制技术

该文把多线性约束和特征空间技术相结合,提出了基于特征空间的多约束最小方差波束形成器(EM-CMVB),该波束形成器可以有效抑制相干干扰。EMCMVB是利用估计得到的相干干扰方向和阵列信号相关矩阵特征分解来得到修改的信号子空间,再把多约束最小方差波束形成器(MCMVB)的权矢量向修改的信号子空间投影来得出新的权矢量。经分析表明,EMCMVB的性能优于MCMVB的性能。最后,给出了计算机仿真结果,证实了EMCMVB的优越性。     

Performance of DMI and eigenspace-based beamformers

The performance of the direct matrix inversion (DMI) method for antenna arrays of arbitrary geometry is analyzed by asymptotic statistical techniques. The effects of eigenspace disturbance caused by finite samples on the output interference and noise powers are examined under the unit gain constraint in the direction of the desired signal. The results show that the performance of the DMI method is degraded mostly by the disturbed noise subspace. That suggests the use of an eigenspace-based beamformer in which the weight vector is computed by using the signal-plus-interference subspace component of the sample correlation matrix. Convergence properties of the eigenspace-based beamformer are evaluated for the cases in which the source number is known and in which it is overestimated. Theoretical analyses validated by computer simulations indicate that the eigenspace-based beamformer has faster convergence rate than the DMI method     

导向矢量和协方差矩阵联合迭代估计的稳健波束形成算法

针对自适应波束形成器在目标导向矢量存在约束偏差时性能急剧下降的问题,该文提出一种目标导向矢量和干扰噪声协方差矩阵联合迭代估计的稳健波束形成算法。该算法首先采用稀疏重构的方法得到目标导向矢量的初始值,并通过从采样协方差矩阵中剔除目标信号估计值完成干扰加噪声协方差矩阵的初始化;然后在建立导向矢量误差优化模型的基础上,采用凸优化方法对目标导向矢量和干扰加噪声协方差矩阵联合迭代求解。最后利用目标导向矢量和干扰加噪声协方差矩阵的稳态估计值获得自适应权矢量。仿真结果表明该算法提高了波束形成器在目标导向矢量约束偏差时的输出信干噪比。     

Effect of pointing errors on the performance of the projectionbeamformer

The projection beamformer generates a steering constraint vector for beamforming by projecting the original steering vector onto the signal-plus-interference subspace of the correlation matrix. This work investigates the effect of pointing errors on the performance of the projection beamformer. A general expression for the output SINR is first derived for the projection beamformer with multiple interferers present. The expression can also be applied to the directional-constraint beamformer except that the steering constraint vector is replaced by the steering vector. Based on the expression for the output SINR, the sensitivity of the projection and the directional-constraint beamformers to pointing errors are examined for the cases of no interferer and a single interferer. Moreover, the performance of the projection beamformer with the source number overestimated is evaluated. Theoretical analysis validated by computer simulations indicates that the projection beamformer performs better than the directional-constraint beamformer, even when the source number is overestimated     

Spatial blocking filter derivative constraints for the generalizedsidelobe canceller and MUSIC

The paper presents a new approach to spatial derivative constraints for the generalized sidelobe canceller (GSC). Spatial derivative constraints have been applied to linearly constrained minimum variance beamformers to reduce the sensitivity to steering error. Earlier approaches to this problem constrained derivatives of the beamformer power and phase response, leading to beamformer performance that depended on the coordinate reference location of the array. Current approaches constrain only the beamformer power response, eliminating the problem with phase dependence. However, nonlinear minimization is required in order to solve for the linear constraint equations. An alternative approach for the GSC, which is presented in the paper, is to use derivative constraints to flatten the null of the spatial blocking filter power response. Thus, for a small steering error, the desired signal is still blocked from the noise cancelling filter, and the GSC output is unaffected by the steering error. These derivative constraints can be used with wideband array calibration, leading to effective performance in the presence of array errors. This same approach to derivative constraints can be used in other applications involving spatial blocking filters, such as the constrained MUSIC direction finding algorithm to give robustness against direction error of the known signal subspace     

宽带子阵域特征空间稳健对角减载波束形成

针对宽带子阵域自适应波束形成器在实际使用中稳健性下降、对弱信号的检测能力受信噪比限制的问题,提出了一种宽带子阵域特征空间稳健对角减载自适应波束形成方法.首先提出利用子阵域特征空间投影法修正导引向量并得到球形不确定集的估计,再利用RCB（Robust Capon Beamformer）算法得到约束条件下的最优权值.另一方面,利用子阵域互谱密度矩阵的最小特征值作为子阵域非相关噪声功率的估计并进行对角减载,以最优权值对减载矩阵波束形成得到子带波束输出,对每个窄子带重复上述处理,再将结果非相干叠加即可得到本文方法的最终结果.理论及实验分析表明方法能提高自适应波束形成器的稳健性及输出信噪比.     

Doubly constrained robust Capon beamformer

The standard Capon beamformer (SCB) is known to have better resolution and much better interference rejection capability than the standard data-independent beamformer when the array steering vector is accurately known. However, the major problem of the SCB is that it lacks robustness in the presence of array steering vector errors. In this paper, we will first provide a complete analysis of a norm constrained Capon beamforming (NCCB) approach, which uses a norm constraint on the weight vector to improve the robustness against array steering vector errors and noise. Our analysis of NCCB is thorough and sheds more light on the choice of the norm constraint than what was commonly known. We also provide a natural extension of the SCB, which has been obtained via covariance matrix fitting, to the case of uncertain steering vectors by enforcing a double constraint on the array steering vector, viz. a constant norm constraint and a spherical uncertainty set constraint, which we refer to as the doubly constrained robust Capon beamformer (DCRCB). NCCB and DCRCB can both be efficiently computed at a comparable cost with that of the SCB. Performance comparisons of NCCB, DCRCB, and several other adaptive beamformers via a number of numerical examples are also presented.     

冲击噪声背景下基于归一化的线性约束特征干扰相消器

针对冲击噪声背景下,常规波束形成算法性能下降的问题,本文提出一种适用于任意未知统计特性的代数拖尾冲击噪声环境下的基于归一化的线性约束特征干扰相消器（N-LCEC）算法。该算法在附加线性约束的条件下,以噪声功率最小化为目标函数;通过对输入信号进行无穷范数归一化,使变换信号的二阶统计量在代数拖尾的冲击噪声环境下存在且有界,然后将自适应权矢量约束于噪声子空间的方法,提高了波束形成器在冲击噪声背景下的性能。N-LCEC算法无需噪声特征指数的先验信息,适用冲击噪声环境更广;N-LCEC算法具有运算简单,干扰抑制能力强,同时保持静态方向图的副瓣特征等优点。仿真结果验证了该算法的有效性和优越性。      

Eigenstructure based partially adaptive array design

A procedure is presented for designing partially adaptive arrays having nearly fully adaptive performance under steady-state conditions. Theory predicts that the required adaptive dimension is less than or equal to the rank of the spatially/temporally correlated portion of the interference correlation matrix for arbitrary linearly constrained minimum-variance beamformers. Knowledge of the eigenstructure of the interference correlation matrix is required to implement a beamformer with this adaptive dimension. To avoid adaptive estimation of the eigenstructure, the eigenstructure of an averaged correlation matrix (which spans the interference scenarios of interest) is utilized, and the adaptive dimension is given by the rank of the averaged correlation matrix. Construction of a transformation for reducing adaptive dimension is addressed. Simulations illustrating the utility of the eigenstructure approach are provided     

Widely linear generalized sidelobe canceling beamforming with variable diagonal loading

We propose a robust widely linear (WL) beamformer for noncircular (NC) signals in the presence of angle of arrival (AOA) errors or array random perturbations. In our beamformer, the block conjugate structure of covariance matrix is exploited to avoid updating the full weight vector, which reduces the computational loads. We add a variable diagonal loading term in the weight vector to improve the robustness of the WL beamformer. Moreover, the orthogonality constraint of block matrix is not required to calculate the amount of diagonal loading. Computer-simulation results show that the proposed WL beamforming provides improved performance over the conventional linear beamformers for NC signals in the presence of AOA errors and array random perturbations.     

A recursive least squares implementation for LCMP beamforming underquadratic constraint

Quadratic constraints on the weight vector of an adaptive linearly constrained minimum power (LCMP) beamformer can improve robustness to pointing errors and to random perturbations in sensor parameters. We propose a technique for implementing a quadratic inequality constraint with recursive least squares (RLS) updating. A variable diagonal loading term is added at each step, where the amount of loading has a closed-form solution. Simulations under different scenarios demonstrate that this algorithm has better interference suppression than both the RLS beamformer with no quadratic constraint and the RLS beamformer using the scaled projection technique, as well as faster convergence than LMS beamformers     

双基地MIMO雷达发射波束形成与多目标定位

针对在导向矢量存在误差情况下自适应波束形成算法性能严重下降的问题, 提出一种基于导向矢量估计的鲁棒自适应波束形成(Steering Vector Estimation Based Robust Adaptive Beamforming, SVE-RAB)算法.算法用导向矢量不确定范围估计真实导向矢量, 利用范数约束通过二阶锥规划技术提高波束形成的鲁棒性.算法可在导向矢量存在误差的情况下, 对期望信号保持最大增益并有效抑制干扰, 且有效提高了波束形成输出的信干噪比(Signal to Interference plus Noise Ratio, SINR).仿真结果验证了算法的有效性和优越性.     

An adaptive generalized sidelobe canceller with derivative constraints

An adaptive broad-band beamforming structure is presented which employs a gradient-based weight adjustment algorithm to minimize output variance subject to a set ofJlinear constraints on broadband directional derivatives in the desired look direction. A generalized sidelobe-cancelling structure is employed in which a nonadaptive (conventional) beamformer operates in parallel with an adaptive beamformer. The conventional portion has a broad-band beampattern which adheres to the specified constraints while the adaptive path is a cascade of a fixed signal blocking matrix and a set of tapped-delay line filters. Blocking is employed to ensure that all incident waveforms which meet the specified constraints do not reach the tapped-delay lines. As a result, an unconstrained least mean square (LMS) power minimization algorithm is employed to adapt the delay line weights. It is shown that with the addition of the directional derivative constraints, the beamformer quiescent bcampattern becomes a function of the location of the phase center used to specify the constraints. A design criterion for choosing this location is suggested and simulation experiments which illustrate the performance of this new adaptive beamformer are presented.     

脉冲噪声下加权稀疏约束稳健波束形成方法

针对脉冲噪声下现有稀疏约束波束形成方法,对不同角度信号施加相同稀疏约束而带来干扰抑制能力有限的问题,本文提出了一种干扰抑制能力更优的加权稀疏约束稳健波束形成方法。该方法首先利用波束方向图的稀疏特性,在最小散度无畸变响应波束形成的目标函数中加入波束方向图l1范数约束;然后采用基于无穷范数归一化方法对阵列接收到的所有快拍信号做自适应预处理,以使预处理后的阵列接收信号协方差矩阵有限;最后运用传统的基于协方差矩阵特征分解的子空间法构造加权矩阵并应用到稀疏约束项中,使得波束方向图中不同角度的信号得到不同程度的约束。实验仿真表明,所提出方法不仅保持相对较低的旁瓣增益,而且显著加深了干扰方向的零陷,提高了输出信干噪比。      

一种快速的特征空间自适应波束形成算法

特征空间自适应波束形成（EBAB）算法的权向量是线性约束最小方差（LCMV）波束形成器的权向量在信号干扰子空间上的投影,因此需要计算量巨大的特征分解。基于信号干扰子空间投影矩阵可利用阵列协方差矩阵进行高精度的有理近似的思想,提出一种快速计算自适应权向量的算法。理论分析和计算机仿真表明,在信号干扰子空间维数已知时,该算法的性能同EBAB算法一致,同时该算法对子空间维数过估计不敏感。     

Experimental and theoretical comparison of some algorithms forbeamforming in single receiver adaptive arrays

Adaptive null steering in single receiver adaptive arrays is discussed. The single receiver structure allows only output power for a given set of weights to be measured. The problem, then, is to adaptively adjust the weights of the antenna array based on output power measurements only so as to reject interference signals while maintaining a fixed response in a given look direction. The authors determine the optimal beamformer weights in a single step, by estimating the covariance matrix of the array sensor outputs using a weight perturbation technique. Based on this covariance matrix estimate, three different approaches for finding the beamformer weights are studied. The first corresponds to a sample matrix inversion scheme, with the sample covariance matrix replaced by the one obtained from the perturbation estimation method, while in the second approach the weights are determined using an eigenvalue decomposition of the covariance matrix estimate. In the third approach the directions-of-arrival (DOAs) of the incoming wavefronts are first estimated, and then, in a second step, the beamformer weights are calculated from the DOA estimates. The advantage of the third approach is that this method is not affected by correlation between the different sources     

基于特征结构的自适应波束形成新算法

基于相关矩阵的特征分解，本文提出了一种改进的线性约束最小方差波束形成（ＬＣＭＶ）新算法，当目标信号含于相关矩阵中时，新算法能有效地抑制信号对消现象，并且具有良好的波束保形能力和快速收敛特点，计算机仿真结果验证了这些优点。