基于干扰协方差矩阵重构的恒定束宽鲁棒自适应波束形成

针对宽带波束形成中的恒定束宽波束响应优化设计问题与鲁棒性问题展开研究。首先,提出一种基于相位补偿的恒定束宽全局优化设计方法,通过对阵列流形向量进行相位补偿来设计恒定束宽波束,与现有的一些方法相比,该方法不仅能获得全局最优解,而且物理实现简单。同时,还提出一种基于协方差矩阵重构的鲁棒自适应宽带波束形成算法。该算法采用Capon估计器估计样本数据的空间一频率谱密度函数,然后对期望信号波达方向之外的角度区间进行积分来重构干扰加噪声协方差矩阵,最后利用重构的协方差矩阵设计自适应波束形成器权系数。该波束形成器设计问题被表述成凸优化问题求解。仿真结果表明,在整个输入信噪比范围内,该算法几乎都能获得接近理想值的输出信干噪比。      

协方差矩阵重构的稳健自适应波束形成算法

针对协方差矩阵含有期望信号成分以及波束指向角失配时,传统自适应波束形成器性能严重下降的问题,提出了协方差矩阵重构的稳健自适应波束形成算法。该算法将全空域划分成若干互不重叠的区域,分别对应干扰区域与信号区域,先利用Capon波束形成器对干扰区域积分,由此构造出干扰协方差矩阵。然后,利用标准Capon波束形成器的波束域MUSIC谱估计法对信号区域积分,重构出信号协方差矩阵,以其主特征向量作为期望信号导引向量估计。由于算法重构了干扰加噪声协方差矩阵并对导引向量进行了修正,保证了自适应波束形成器的性能。理论分析和仿真实验结果表明,算法在训练数据含有期望信号成分和波束指向角度失配情况下具有良好的性能。      

圆环形传感器阵列超指向性频率不变响应波束优化方法

提出了一种适用于圆环形传感器阵列的超指向性频率不变响应波束优化方法。首先,基于前期在最小均方误差准则下得到的不同频率处权值向量与期望波束权值向量的解析函数关系,将指向性因子、误差敏感度函数和最小均方误差进一步表达成了期望波束权值向量的函数;然后,构建了一个多约束优化问题,获得了满足指向性、稳健性、频率不变性等约束条件的最优期望波束,由此合成得到了最优宽带频率不变响应超指向性波束,并给出了相应的仿真和实验结果。      

Research and application of fast-convergent minimum variance distortionless response algorithm

The conventional MVDR adaptive beamformer is a high-resolution narrowband beamformer which estimates the optimal beamforming weights using narrowband CSDM of real acoustic field.In practical applications,MVDR algorithm needs long observation time to estimate the covariance matrix.This inherent property makes it difficult to localize fast-moving targets.For wideband signals,MVDR algorithm needs inverting every CSDM which increases the computational demands.For correlated sources,the performance of MVDR will degrade dramatically because the signals will cancel each other.A fast-convergent MVDR algorithm based on subband subarray processing is proposed.The full frequency band is divided into sets of subbands and the line array is divided into sets of subarrays.For every subband the STCM of reduced dimensions is calculated.Then adaptive beamforming weight of fast-convergent MVDR algorithm and spatial spectrum estimation are obtained.At the same time,spatial spectrum estimation can be made for correlated sources using the two-sided spatial smoothing method. Results of simulation and trial data show that the proposed method has high-resolution and near-instantaneous convergence property,two-sided spatial smoothing has satisfactory validity of decorrelation.     

基于半定规划和秩-1分解的稳健波束形成

针对标准Capon波束形成器在存在导向矢量失配时性能急剧下降问题, 提出了一种基于半定规划和秩-1分解的稳健波束形成算法. 该方法通过对实际导向矢量的估计提高自适应波束形成算法稳健性. 首先分别从干扰抑制和噪声抑制两个方面推导了新导向矢量应满足的约束条件, 并证明了利用矩阵滤波器构造约束条件的合理性; 构造了估计最优导向矢量的优化问题并将其转化为易于求解的松弛半定规划问题, 同时引入秩-1分解理论用于优化问题的求解. 仿真分析表明, 与目前较为常见的算法相比, 本文算法只需利用期望信号可能入射区间这一先验信息, 能获得更高输出信干噪比和功率估计精度. 关键词： 稳健自适应波束形成 半定规划 秩-1分解 导向矢量估计     

快速收敛最小方差无畸变响应算法研究及应用

常规最小方差无畸变响应(MVDR)自适应波束形成是一种高分辨窄带波束形成器,它是利用实际声场的窄带互谱密度矩阵(CSDM)估计出自适应波束形成权向量。在实际应用中,MVDR算法需要较长的观测时间估计协方差矩阵,不利于对高速运动目标进行定位;对于宽带目标信号,MVDR算法需要对每一个CSDM进行求逆运算,计算量较大;在相干源条件下,目标信号之间会发生"对消"现象,MVDR算法性能急剧恶化。本文提出了基于子带子阵处理的快速收敛MVDR自适应波束形成方法。首先将全频带划分成一组子带,将接收线阵划分成一组子阵,然后对每一子带计算降维的驾驶协方差矩阵(STCM),从而得到快速收敛MVDR自适应波束形成的权值和空间谱估计结果。同时采用双向空间平滑方法对相干源进行MVDR空间谱估计。仿真和海试数据处理结果表明该算法在保证高分辨力的同时,具有瞬时收敛的性能,双向空间平滑技术具有良好的解相干性能。      

有源声呐距离维波束形成方法

针对脉冲压缩处理所获得的距离分辨率和干扰抑制能力不足的问题,提出了有源声呐距离维波束形成方法。该方法从单个脉冲回波的频域输出中提取多组子带分量,每个子带分量的中心频率形成等差数列,对应的相移形成复指数等比数列(可类比于均匀直线阵的阵列流形向量)。根据这一特点,使用多组子带分量构建协方差矩阵,根据中心频率设计距离维加权向量,建立了距离维波束形成模型。给出了距离维常规波束形成和距离维自适应波束形成的表达式、处理流程,对距离分辨率和干扰抑制能力进行了分析。利用数值仿真和水池实验证明,距离维常规波束形成可获得与脉冲压缩处理类似的距离分辨率,而距离维自适应波束形成可获得更高的距离分辨率和更优的距离维干扰抑制能力。      

波束空间能量约束的稳健自适应波束形成

为改善波束形成器在一定失配条件下的工作性能,提出了一种稳健自适应波束形成方法。该方法通过设计信号在波束空间能量分布的约束条件,利用阵列数据协方差矩阵,结合迭代二阶锥规化方法,实现信号驾驶向量的估计,最后利用该估计得到最小方差无失真响应波束形成器。该方法在较恶劣的失配条件下也可以自适应地准确估计信号驾驶向量并保证其成分无失真地通过,使系统的稳健性得到改善。数据仿真结果表明,该方法在理想条件下与成熟的对角加载法性能相当,在失配条件下则优于后者。      

一种基于模式搜索算法的基阵波束优化方法

波束形成在声纳/雷达信号处理中占有重要的地位,而设计出满足要求的波束形状是声纳/雷达信号空间处理的重要内容。自适应波束形成算法理论上可以获得最优的工作性能,但其计算复杂度高、宽容性差等缺点严重地限制了这些算法的实际应用。本文采用基于模式搜索的波束优化算法,获得了与实际接收数据无关的、类似于窗函数的幅度权系数。与加窗波束形成算法相比,这种方法可以在保证主瓣宽度不展宽的情况下,有效降低旁瓣级,并且,这种方法对基阵的几何形状没有任何限制。     

Nearfield broadband array design using a radially invariant modal expansion

This paper introduces an efficient parameterization for the nearfield broadband beamforming problem with a single parameter to focus the beamformer to a desired operating radius and another set of parameters to control the actual broadband beampattern shape. The parameterization is based on an orthogonal basis set of elementary beampatterns by which an arbitrary beampattern can be constructed. A set of elementary beamformers are then designed for each elementary beampattern and the desired beamformer is constructed by summing the elementary beamformers with frequency and source-array distance dependent weights. An important consequence of our result is that the beamformer can be factored into three levels of filtering: (i) beampattern independent elementary beamformers; (ii) beampattern shape dependent filters; and (iii) radial focusing filters where a single parameter can be adjusted to focus the array to a desired radial distance from the array origin. As an illustration the method is applied to the problem of producing a practical array design that achieves a frequency invariant beampattern over the frequency range of 1:10 (which is suitable for speech acquisition using a microphone array), and with the array focused either to farfield or nearfield where at the lowest frequency the radial distance to the source is only three wavelengths.     

MASS-RAB: Robust adaptive beamforming for general-rank signal models via matched spatial spectrum processing

The wavefront of acoustic signal suffers from fast fluctuation after a long distance propagation in a random and inhomogeneous ocean channel, which makes the rank of the covariance matrix for the desired signal (signal of interest) remarkably higher than one. Consequently, the assumption of rank-one point signal model for existing adaptive beamforming algorithms is no longer suitable. In this paper, a matched spatial spectrum processing based robust adaptive beamforming (MASS-RAB) algorithm is presented for general-rank signal models. First, the interference-plus-noise covariance matrix and the desired signal covariance matrix are reconstructed using the matched spatial spectrum processing method. Second, the weight vector is directly calculated using these reconstructed covariance matrices for the minimum variance distortionless response (MVDR) algorithm, which is developed for the general-rank signal models. Due to covariance matrix reconstruction, the MASS-RAB algorithm is more robust than those methods relying on the sample covariance matrix. The cases of the rank-one point signal model and the full-rank non-point signal model are considered by several numerical examples. Experimental results have demonstrated the superiority of the proposed MASS-RAB method.     

基于DFT插值的线性约束最小方差宽带自适应阵列

本文提出一种具有频率不变波束图的线性约束最小方差宽带自适应算法。首先给出了具有频率不变波束图的连续线阵的灵敏度函数与离散线列阵加权系数之间的关系，然后给出了使用DFT插值法求解各子带阵列权系数的方法，最后将DFT插值法应用于线性约束最小方差宽带自适应阵列。理论分析及仿真结果表明，该算法可以在实现最小方差波束形成的同时保持波束图基本不随频率变化，且该方法可以降低宽带自适应阵列的运算量。     

Robust adaptive acoustic vector sensor beamforming using automated diagonal loading

In this paper, a novel robust adaptive acoustic vector sensor beamformer based on shrinkage is derived. Unlike many existing methods, the proposed method is completely automatic (or so-called user parameter-free), which means, it do not need the choice of user parameters. The proposed diagonal loading algorithms use shrinkage-based covariance matrix estimates, instead of the conventional sample covariance matrix, in the standard Capon acoustic vector sensor beamforming formulation. The numerical results show that our method is robust against errors on the steering vector and small sample sizes, and meanwhile gives high output signal to interference plus noise ratio (SINR).     

一种最差情况下性能最优化的特征分析自适应波束形成方法

自适应波束形成在弱目标检测和空域滤波中应用广泛。然而在实际海洋环境中,失配情况比较普遍,往往会导致传统自适应波束形成方法性能明显下降。针对此问题,本文基于特征分析重构观测信号协方差矩阵来抑制干扰对弱目标检测的影响,在此基础上进一步利用凸优化算法来提高波束形成方法的鲁棒性。数值仿真和海试数据处理结果表明,本文所提方法在抑制干扰对弱目标影响的基础上,在阵元位置平均误差不超过入射信号中心频率对应波长的40%的情况下,仍可以鲁棒地检测目标信号。同时,该方法显著提高了自适应波束形成方法的输出信干噪比,且受对角加载量取值的影响较小。      

Design of broadband beamformers based on an expected response interpolation technique

A method for designing broadband beamformers based on an expected response interpolation technique was proposed, with the aim of reducing the heavy optimization burden in the broadband beamformer design problem. In the method, some typical frequencies in the designing frequency band are selected and the optimal array weights are designed on these typical frequencies, based on which a broadband expected response function is constructed. Then, FIR filters are designed to realize the broadband beamforming over the whole designing frequency band, via the interpolation technique which is utilized to the expected responses of the FIR filters. Broadband beamforming can be fulfilled by applying these filters to each of the sensors in the array. By using the proposed method, designers need not to divide the whole designing frequency band into narrow subbands so as to make the narrow band assumption valid, which not only reduces the heavy designing burden, but also releases the requirement for measurements at fine frequency grids in the robust beamformer design. Results of both computer simulations and watertank experiments verify the effectiveness of the proposed method.     

可变不确定集约束的鲁棒自适应波束形成方法

自适应波束形成方法在存在协方差矩阵误差和导向向量误差的失配条件中性能严重下降。最差情况性能最优。(Worst-Case Performance Optimization,WCPO)方法可以显著增强失配条件下自适应波束形成的鲁棒性,但该方法存在系统性的信号功率过估计问题,并且限定协方差矩阵不确定集与导向向量不确定集的两个关键参数需要人为指定,缺乏具备明确物理意义的求解方法和数据自适应性.本文以WCPO方法为基础,给出了信号功率过估计的理论分析以及相应的改进方法,提出了基于矩阵重构的协方差矩阵不确定集参数的自适应估计方法,最终得到一种可变不确定集约束的鲁棒自适应波束形成方法(WCPO-PCVC).相比WCPO方法,该方法消除了信号功率估计的系统性偏差,且关键参数无需人为指定。数值仿真和海试数据处理结果表明,该方法在失配条件下具有良好的干扰与旁瓣抑制能力,与常规波束形成方法相比具有更好的信号到达角分辨能力,与自适应波束形成方法相比估计的信号功率更为精准。      

一种新的稳健波束形成算法及其一维搜索策略

存在条件失配时自适应波束形成器的性能急剧下降,凸优化技术的引入使稳健波束形成器的设计更加灵活,但同时带来了计算复杂度的增加和工程实现上的困难.针对上述问题,提出了一种基于最小二乘估计的稳健波束形成算法,并推导得到一种基于一维搜索的求解方法.首先利用广义旁瓣对消器的结构将标准Capon波束形成器转化为稳健最小二乘问题,并将该问题转化为二阶锥规划的形式.为了减少计算量,利用二阶锥规划问题的原始问题和对偶问题的关系,将求解过程转化为一维搜索,并利用牛顿迭代法获得最优解,从而获得与标准Capon波束形成相近的计算复杂度.仿真分析表明,该算法具有良好的抗导向矢量失配和快拍数不足的稳健性.     

Adaptive microphone array for unknown desired speaker's transfer function

The main drawback of minimum variance distortionless response (MVDR) beamformer is the cancellation of the desired speech signal and its degradation in multi-path wave propagation environment. To make the adaptive algorithm robust against room reverberation and to prevent desired signal cancellation an estimation of unknown desired speaker's transfer function was proposed. The estimation is based on the signal and the interference covariance matrices. The estimated transfer function is then applied to the MVDR beamformer. The proposed algorithm was tested on a simulated room with reverberation. The results showed better quality of the restored speech compared to some typical adaptive algorithms.     

有距离辨识度的传声器阵列波束优化算法研究*

小尺度线性传声器阵列在便携式通信设备中具有潜在应用前景,其波束优化算法大多关注于抑制来自与声源不同方向的噪声,而不能有效地抑制与声源同方向的噪声。本文通过对几种典型波束优化策略进行改进,增加线性约束条件,使得阵列兼具方向和距离辨识度。论文对比了几种优化方法的波束性能,同时讨论了约束条件对波束旁瓣的影响,并提出了鲁棒性的优化方案。仿真结果显示,合理的优化策略和线性约束条件可以使阵列波束获得很好的聚焦性能。     

一种加权稀疏约束稳健Capon波束形成方法

为了克服标准Capon波束形成器旁瓣级高以及存在角度失配时性能急剧下降等缺点, 在稀疏约束Capon波束形成器的基础上, 提出了一种加权稀疏约束Capon波束形成器. 该方法利用波束响应的稀疏分布特性, 在标准Capon波束形成优化模型中加入旁瓣区域波束响应稀疏约束(l₁ 范数约束), 使旁瓣区域波束响应向量中非零元素的个数最小化; 通过阵列采样数据协方差矩阵特征分解得到信号子空间及噪声子空间, 利用信号子空间与噪声子空间的正交特性, 构造加权矩阵对稀疏约束进行加权, 使得稀疏重构时波束响应向量中不同角度对应的元素得到不同程度的约束. 该方法有效地抑制了Capon波束形成器的高旁瓣级, 加深了干扰方位零陷, 提高了阵列输出信干噪比. 由于稀疏约束, 波束响应向主瓣集中, 期望信号方向附近的波束响应都较大, 从而也提高了阵列抗导向矢量角度失配的能力. 数值仿真和水池实验验证了所提方法的有效性.