面向二元麦克风小阵列改进的广义旁瓣抵消器语音增强算法

二元麦克风小阵列在手机、助听器等受空间、成本以及运算能力限制的设备中被广泛研究用以提高目标语音质量。二元麦克风小阵列中语音增强算法主要包括波束形成方法以及相干性滤波器方法。波束形成方法的思想是利用目标声源相对阵列的位置关系获取相应的时域和空域信息,可以保留目标声源方向的信号而抑制其他方向的干扰信号;相干性滤波器方法则通过阵元间不同信号的相关性进行噪音抑制。考虑这两种类型方法的优点,本文提出一种面向二元麦克风小阵列改进的广义旁瓣抵消器语音增强算法,通过在广义旁瓣抵消器的固定波束形成支路上使用相干性滤波器,提高固定波束形成输出信号的信噪比,然后在广义旁瓣抵消器自适应支路利用阵列的时域和空域信息对固定波束形成支路输出的信号中残余噪音进行估计,进而获得增强后目标输出信号。仿真和实际试验表明,本文提出的算法明显优于单独使用小阵列波束形成算法和相干性滤波器算法。      

An algorithm for linearly constrained adaptive array processing

A constrained least mean-squares algorithm has been derived which is capable of adjusting an array of sensors in real time to respond to a signal coming from a desired direction while discriminating against noises coming from other directions. Analysis and computer simulations confirm that the algorithm is able to iteratively adapt variable weights on the taps of the sensor array to minimize noise power in the array output. A set of linear equality constraints on the weights maintains a chosen frequency characteristic for the array in the direction of interest. The array problem would be a classical constrained least-mean-squares problem except that the signal and noise statistics are assumed unknown a priori. A geometrical presentation shows that the algorithm is able to maintain the constraints and prevent the accumulation of quantization errors in a digital implementation.     

基于空时二维协方差矩阵修正的波束形成算法

在实际应用环境中,信源和阵列传感器等存在误差,假设期望信号的导向矢量与真实信源导向矢量的失配会导致阵列波束形成器把期望信号当作干扰来加以抑制。针对信号匹配误差导致自适应波束形成性能下降的问题,提出了一种基于空时二维协方差矩阵修正的波束形成算法,利用空时结构对宽带幅相误差校正的特性,对空时二维协方差矩阵进行重构,并对修正协方差矩阵进行特征值分解,分离出信号加干扰子空间,将失配导向矢量投影可使期望信号与噪声子空间严格正交,最后求解算法最优权值。算法有效改善了波束形成的输出信噪比,计算机仿真验证了理论分析的正确性和算法的稳健性。     

均匀先验分布Bayesian自适应波束形成方法

针对UUV舷侧阵存在观测信号方向有误差的情况，提出了基于均匀先验分布的Bayesian自适应波束形成方法（UB）。该方法假设期望信号的到达方向是区间内服从均匀先验分布的一个变量，利用含有均匀先验分布信息的阵列接收数据和Bayesian后验分布来估计期望信号的到达方向，最后计算权矢量。仿真结果表明，该方法对观测信号方向误差具有较好的稳健性，其阵列方向图的主波束不受观测方向误差的影响，始终对准信号的到达方向，其输出信干噪比随着输入信噪比、快拍数的增加而稳定增加，随着观测方向误差的增大而保持稳定的恒定值。      

稳健的宽带多径干扰抑制波束形成算法

针对传统宽带多径干扰抑制波束形成算法计算量大、稳健性差的问题,提出一种基于均匀直线阵的稳健宽带多径干扰抑制波束形成算法。当期望信号垂直入射时,该算法首先在波束旁瓣区域引入虚拟干扰源构造能量聚焦矩阵,通过主瓣宽度的迭代处理,整体控制输出波束的旁瓣级,将旁瓣区域能量聚焦到主瓣区域,实现多径干扰条件下的宽带波束形成;然后对期望信号和辅助方位角施加相位响应约束,将其扩展至期望信号非垂直入射和存在指向误差的情况,与传统宽带多径干扰抑制波束形成算法相比,在提高算法稳健性的同时大大降低了计算复杂度;最后仿真分析与实际数据验证表明,该算法能够有效的抑制多径干扰,稳健性较好且具有较高的输出信干噪比。      

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.     

拥挤干扰环境下的一种多载波扩频信号接收波束成形方法

针对拥挤干扰环境中的多载波扩频通信系统,提出了一种基于期望信号波达方向估计和干扰功率空间谱分析的波束成形方法。该方法首先利用多载波扩频调制信号的频率分集特性估计期望信号的波达方向,然后利用空间谱分析估计干扰信号的空间功率分布,在此基础上完成波束成形。该方法能够在拥挤强干扰环境下精确估计信号的波达方向,从而保证了干扰信号空间谱估计的有效性。仿真结果表明,即使干扰信号的功率显著强于期望信号,本算法仍然能够精确地估计出期望信号的波达方向,从而保证算法的有效性。     

一种稳健的稀疏Capon波束形成算法

常规Capon波束形成算法具有相对较高的旁瓣增益,且在期望信号导向矢量存在失配时,阵列输出性能下降甚至失效。为解决这一问题,引入了稀疏约束Capon波束形成算法,该算法降低了旁瓣,对期望信号来向不确定具有一定稳健性,但在幅相误差、期望信号指向偏差等多种误差同时存在的情况下其性能下降。本文在稀疏约束Capon波束形成算法基础上,给出了一种稳健的稀疏Capon波束形成算法。该算法主要是在最差性能最优化的情况下,在稀疏Capon上增加了一个导向矢量存在偏差的约束条件。通过计算机仿真,验证了新算法在多种误差环境下的有效性与优越性。     

CDMA中小扩频增益下波束形成

针对CDMA系统中扩频增益较小和用户数较多时信号阵列响应估计精度较差的问题,提出了利用基站收到的码元序列与解扩后的接收序列通过加窗构造新序列来进行波束权值估计的新方法。理论分析与仿真结果表明,该方法能够减少阵列响应的估计对扩频增益和功率控制的敏感性,当用户数大于15时能使输出SINR比现有的码滤波方法平均提高2．5dB。     

Robust Least Squares Constant Modulus Algorithm to Signal Steering Vector Mismatches

The linearly constrained least squares constant modulus algorithm (LSCMA) may suffer significant performance degradation and lack robustness in the presence of the slight mismatches between the actual and assumed signal steering vectors, which can cause the serious problem of desired signal cancellation. To account for the mismatches, we propose a doubly constrained robust LSCMA based on explicit modeling of uncertainty in the desired signal array response and data covariance matrix, which provides robustness against pointing errors and random perturbations in detector parameters. Our algorithm optimizes the worst-case performance by minimizing the output SINR while maintaining a distortionless response for the worst-case signal steering vector. The weight vector can be optimized by the partial Taylor-series expansion and Lagrange multiplier method, and the optimal value of the Lagrange multiplier is iteratively derived based on the known level of uncertainty in the signal DOA. The proposed implementation based on iterative minimization eliminates the covariance matrix inversion estimation at a comparable cost with that of the existing LSCMA. We present a theoretical analysis of our proposed algorithm in terms of convergence, SINR performance, array beampattern gain, and complexity cost in the presence of random steering vector mismatches. In contrast to the linearly constrained LSCMA, the proposed algorithm provides excellent robustness against the signal steering vector mismatches, yields improved signal capture performance, has superior performance on SINR improvement, and enhances the array system performance under random perturbations in sensor parameters. The on-line implementation and significant SINR enhancement support the practicability of the proposed algorithm. The numerical experiments have been carried out to demonstrate the superiority of the proposed algorithm on beampattern control and output SINR enhancement compared with linearly constrained LSCMA.     

The maximin algorithm for adaptive arrays and frequency-hopping communications

An algorithm is described for maximizing of the signal-to-interference-plus-noise ratio (SINR) at the output of an adaptive array. The algorithm discriminates between the desired signal and any interference on the basis of the spectral characteristics of frequency-hopping signals. The algorithm maximizes the SINR by maximizing the desired.signal output power while simultaneously minimizing the interference-plus-noise output power. Rapid convergence of the weights to the steady-state values is achieved by the adjustment of the loop gain as a function of the estimated SINR at each iteration. Implementation of the algorithm in conjunction with a frequency-hopping modem is explained. Computer simulation results describe both the steady-state and transient responses of the system under various jamming conditions. The results indicate a rapid dynamic response and the steering of deep nulls over a wide range of the SINR.     

极化域-空域联合的四元数APES波束形成算法

为了得到稳定的波束方向图、进一步提高极化敏感阵列的滤波性能,文中提出了一种极化域 空域联合的四元数幅度相位估计(Q-APES, Quaternion-Amplitude and Phase EStimation)自适应波束形成算法。首先,利用四元数信号模型很好的保持了两分量阵列各阵元输出信号分量之间固有的正交特性,使得该模型较传统的长矢量模型更适合于极化敏感阵列信号处理。然后,将纯空域的APES算法拓展到极化域-空域联合处理中,给出了Q-APES算法的理论推导和分析,得出了四元数最优滤波权向量,并通过仿真实验验证了文中算法的有效性。计算机仿真结果表明,在强期望信号、低采样快拍数或是入射干扰信号与期望信号相干的情况下,文中算法都可以很好的实现极化域-空域联合自适应滤波。      

基于SMI－CMA联合自适应算法的性能分析

恒模算法(CMA)被广泛地应用到盲自适应波束形成中，除了传输信号波形具有恒定的包络外．CMA不需要先验知识。基于SMI—CMA算法的恒模(CM)阵列级联的结构，由SMI算法决定CMA的初始权向量．系统可以分离多个同信道信源，在干扰信号较强时，仍有稳定的SINR输出，具有较好的收敛速度。仿真结果也证明了SMI—CMA算法具有较强的稳健型和较快的收敛速度。     

Efficient robust adaptive beamforming for cyclostationary signals

This paper deals with the problem of robust adaptive array beamforming for cyclostationary signals. By exploiting the signal cyclostationarity, the LS-SCORE algorithm presented in a paper by Agee et al. (1990) has been shown to be effective in performing adaptive beamforming without requiring the direction vector of the desired signal. However, this algorithm suffers from severe performance degradation even if there is a small mismatch in the cycle frequency of the desired signal. In this paper, we first evaluate the performance of the LS-SCORE algorithm in the presence of cycle frequency error (CFE). An analytical formula is derived to show the behavior of the performance degradation due to CFE. An efficient method is then developed based on the fact that the array output power approaches its maximum as the CFE is reduced. We formulate the problem as an optimization problem for reducing the CFE iteratively to achieve robust adaptive beamforming against the CFE. Simulation examples for confirming the theoretical analysis and showing the effectiveness of the proposed method are provided     

基于DOA估计的RLS-CMA算法

恒模算法被广泛地应用到盲自适应波束形成中,除了传输信号波形具有恒定的包络外,恒模算法不需要先验知识。提出一种基于来波方向估计的递推最小二乘恒模算法,基于恒模阵列级联的结构,由递推最小二乘算法决定恒模的初始权向量,同时通过对权向量多项式求根获得下一级的初始权向量,再利用最小二乘恒模迭代几步获得准确的结果。系统可以分离多个同信道信源,在干扰信号较强时,仍有稳定的信干比输出,并对阵列幅相差不敏感。计算机仿真证明了算法的正确性和有效性。     

An adaptive array utilizing an adaptive spatial averaging technique for multipath environments

When the interference is coherent with the desired signal, the conventional adaptive arrays working under the guiding principle of output power minimization tend to cancel the desired signal by using the coherent interference. A technique is described which enables the adaptive array to function even under such an environment. The array is divided into subarrays, whose input correlation matrices are adaptively averaged so as to produce a Toeplitz matrix which would be obtained when the interference did not correlate with the desired signal. The averaged matrix is now free from correlation terms between the desired signal and interference, and therefore may be used to derive the optimum weight for the array element just as in the ordinary radio environment of incoherent interference. Numerical examples show that the new adaptive array is highly capable to suppress the coherent interferences as well as incoherent ones.     

基于粒子群优化的数字波束形成算法

波束形成的加权系数求解是一个优化过程,现有算法大多经过多次迭代,计算量大,实现复杂。为降低波束形成算法复杂度,将粒子群优化原理应用于数字波束形成中,提出了基于粒子群优化的自适应数字波束形成算法。该算法将每一组权值作为一个粒子,将阵列加权和的输出信号与干扰噪声比(SINR)作为适应度函数,通过比较各个粒子的适应度值,进行迭代搜索得到最优解。该算法可使天线阵在主波束对准有用信号,同时能有效抑制两个以上的干扰,且对阵列通道误差有较好的稳健性。计算机仿真验证了算法的有效性。     

On the performance of a polarization sensitive adaptive array

The ability of a least mean square (LMS) adaptive array to adapt to the electromagnetic polarization of incoming signals is considered. An array of two pairs of crossed dipoles is studied. A desired signal and an interference signal are assumed to arrive from arbitrary directions with arbitrary elliptical polarizations. The output signal-to-interference-plus-noise ratio (SINR) from the array is computed as a function of the signal angles of arrival and polarizations. It is shown that as long as certain special desired signal polarizations are avoided, the array is difficult to jam with a single interference signal. To produce a poor SINR, an interference signal must both arrive from the same direction and have the same polarization as the desired signal.     

The tripole antenna: An adaptive array with full polarization flexibility

The performance of an adaptive array using three mutually perpendicular dipoles (a "tripole") is studied. A desired signal and an interference signal, each with arbitrary angle of arrival and polarization, are assumed incident on the array. Uncorrelated thermal noise is also assumed present on each element signal. The output desired signal-to-interference-plus-noise ratio (SINR) is computed as a function of the signal arrival angles and polarizations. It is shown that for most angles of arrival and polarizations, the array has an excellent ability to protect a desired signal from interference. Certain special cases where the performance is not good are discussed in detail.     

Least-squares regenerative hybrid array for adaptive beamforming

The least-squares method is applied to adaptive beamforming in a regenerative hybrid array that utilizes both the steering vector and reference signal acquired from the array output to preserve the desired signal. It is shown that like the gradient-search-based regenerative hybrid array, the proposed array converges to the steady state of the Applebaum-type array adapted without the desired signal present. The array transient behavior is simulated with weights updated by the QR decomposition algorithm. Results show that the least-squares regenerative hybrid array converges much faster than the original regenerative hybrid array on which it is based. Simulations of the steady-state performance show that the regenerative hybrid array performs better than high-order derivative constraint arrays