互质阵列信号处理研究进展:波达方向估计与自适应波束成形

阵列信号处理是雷达领域各类应用的核心技术之一。近年来,互质阵列的提出打破了传统方法受限于奈奎斯特采样速率这一瓶颈,其稀疏布设的阵列结构和互质欠采样的信号处理方式大幅降低了系统所需的软硬件开销,为当前不断提升的实际应用需求提供了理论基础和技术前提。鉴于其在自由度、分辨率及计算复杂度等方面的性能优势,互质阵列信号处理的理论和技术研究受到了国内外学者的广泛关注。该文分别从波达方向估计和自适应波束成形这两个阵列信号处理领域的基本问题出发,介绍了互质阵列信号处理方向的研究进展。在互质阵列波达方向估计方面,该文总结了互质子阵分解方法和虚拟阵列信号处理方法等两类典型技术路线,并以此为基础介绍了压缩感知和无网格化技术在低复杂度和超分辨估计等方面的最新研究工作。在互质阵列波束成形方面,该文剖析了其与互质阵列波达方向估计问题的区别与联系,并介绍了面向互质阵列的高效鲁棒自适应波束成形设计方法。该文旨在通过对互质阵列信号处理研究前沿的分类归纳和总结,探讨各类方法的优势和未来的研究方向,为其在雷达等领域的产业需求和实际应用提供理论和技术参考。      

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.     

一种联合修正的稳健Capon波束形成算法

指出了水平定向天线阵波束形成的主要难点,没有固定相位中心和受交叉极化来波的影响。阵列受随机性误差使得导向矢量存在较大失配,从而导致传统Capon算法性能下降甚至失效。在阵列误差模型下,给出了基于协方差矩阵与导向矢量联合修正的稳健Capon波束形成算法。该算法首先基于收缩得到一个增强的协方差矩阵,然后通过最大化Capon输出功率实现对导向矢量的修正,同时增加二次型约束防止修正的导向矢量接近于干扰导向矢量上。该算法可转化为二次约束二阶规划问题,并通过凸优化进行求解。仿真结果表明,该算法对天线阵模型中误差矩阵具有一定的稳健性,且较其他稳健算法具有较好的性能。     

基于均匀同心圆阵列的近场宽带波束形成

该文提出了一种频率不变近场宽带波束形成的方法。该方法将均匀同心圆阵列的输出经傅里叶逆变换转换成相位模式信号,并经过近场矫正和频率补偿网络,可达到频率响应不变的远场阵列响应效果。在此基础上,该文将传统远场窄带波束形成法推广到近场宽带阵列中。仿真结果表明,该文提出的近场宽带阵列响应具有近似频率响应不变的效果,其波束图也接近远场窄带阵列波束图。另外,与其他几种波束形成方法相比,基于该文提出的频率不变近场宽带阵列提升了波束形成性能,且具有较低的计算复杂度。     

Broadband beamforming using Laguerre filters

Space-time processing is a well-substantiated method for designing broadband beamformers. In the conventional Frost space-time beamformer, tapped delay line (TDL) filters are used in each branch of the array to create a wideband response for interference suppression. In this article a new space-time beamforming method is introduced in which Laguerre filters replace the traditional TDL filters in the Frost beamformer. The Laguerre filters are fundamentally IIR filters but with only one pole in their structure. Unlike other IIR-based space-time beamforming methods, the proposed method does not need an adaptive procedure for the pole adjustment and is inherently stable. Simulation results show superior performance of the proposed method compared to the Frost beamformer and comparable results against other IIR-based beamformers with much less computational complexity and guaranteed stability.     

Successive beamforming,multiuser detection and diversity reception for multicarrier DS-CDMA system with antenna array

Code-Division Multiple-Access (CDMA) systems are interference limited,and therefore efficient interference management is necessary to enhance the performance of a CDMA system.In this paper,a successive beamforming (spatial filtering),linear decorrelating MultiUser Detection (MUD, temporal filtering) and diversity reception structure for uplink multicarrier Direct Sequence CDMA (DS-CDMA) system with antenna array are proposed.By beamforming,the antenna array suppresses interference according to the distinct array signature.Subsequently,linear decorrelating MUD is ap- plied to separate the signals of different users and eliminate Multiple Access Interference (MAI).Finally, the decorrelated signals at different subcarriers that belong to the same user are combined to achieve frequency diversity.Simulation results show that the proposed structure offers significant Bit Error Rate (BER) performance improvement by successively exploiting the space-time-frequency processing.     

非均匀傅里叶变换频率不变波束形成方法

频率不变波束形成是宽带阵列信号处理研究的重要内容之一。本文以麦克风阵列语音处理为研究对象,针对FIB低频处波束形成一致性不理想的问题,提出了一种基于非均匀傅里叶变换的频率不变波束形成方法。该方法采用非均匀采样来增加低频处的采样点数,构建符合非均匀傅里叶逆变换的范德蒙矩阵,再用优化对称窗函数对变换结果进行截取,得到空时滤波器。该方法不仅实现了低频段与期望波束响应近似的波束图,且降低了阵元数目。计算机仿真实验结果验证了该方法的有效性。      

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.     

Design of two-dimensional rectangular array beamformers withpartial adaptivity

This paper considers the problem of designing a two-dimensional (2-D) rectangular array beamformer with partial adaptivity. Using the eigenstructure of the signal data received by a 2-D rectangular array beamformer, we first show that the optimal weight matrix when using full adaptivity can be obtained from a set of singular vectors. Then the design problem of using partial adaptivity is formulated. As a result, the optimal solution for the partially adaptive weight matrix can be found by solving two basic problems, namely determining the proper dimension of the partially adaptive weight matrix and the set of the singular vectors. We develop the detection formulas for the information theoretic criteria AIC and MDL to find the proper dimension. Next, an efficient method is presented so that the optimal solution for the set of the singular vectors can be found analytically. We also investigate the required computational complexity. It is shown that 2-D partially adaptive beamforming using the proposed technique requires less computational complexity than 2-D fully adaptive beamforming using conventional techniques. Moreover, computer simulations demonstrate that the proposed 2-D partially adaptive technique provides satisfactory array performance when compared with conventional fully adaptive techniques     

Extending the concept of IIR filtering to array processing using approximate spatial IIR structure

Various array processing techniques applied to uniform linear arrays are involuntarily realized using structures that are analogous to finite impulse response filters. This observation leads to the following question: “can we extend infinite impulse response (IIR) filtering to array processing?”. In this paper, we introduce the concept of IIR array in spatial domain. Note that IIR array here does not mean time-domain IIR filtering for array beamforming which is commonly understood. This paper is dedicated to the study of an alternate approach for array signal processing which defines IIR structure in spatial domain. To illustrate the applicability of the concept of IIR array, we propose a new direction-of-arrival estimation technique as well as a beamformer with the spatial domain IIR array implementation. The performance of the proposed methods are comparable to the existing techniques. These illustrations are intended to introduce a new approach which potentially can offer more degrees of freedom to control the performance of the array and reduce the complexity of the system for a desired performance.     

A novel adaptive beamforming algorithm for antenna array CDMA systems with strong interferers

Blind beamforming based on the maximum signal-to-noise ratio (MSNR) can improve the performance of an array system only when the processing gain of the given code-division multiple-access (CDMA) system is high enough such that the desired signal can become dominant after despreading (see Choi, S. and Shim, D., IEEE Trans. Veh. Technol., vol.49, p.1793-1806, 2000; Choi, S. and Yun, D., IEEE Trans. Antennas Propagat., vol.45, p.1393-1404, 1997). We consider a maximum signal-to-interference-plus-noise ratio (MSINR) beamforming. The MSINR performance criterion is chosen to deal with strong interferers effectively. It is shown that blind MSINR beamforming is possible by directly utilizing the input and output signals of correlators of the CDMA systems. In addition, we propose an adaptive beamforming algorithm at a lower computational complexity - about O(7.5N) - where N is the number of antenna elements of the array system. Simulation results are presented in various signal environments to show the performance of the proposed adaptive algorithm.     

Estimation of radio refractivity structure using matched-fieldarray processing

In coastal regions the presence of the marine boundary layer can significantly affect RF propagation. The relatively high specific humidity of the underlying “marine layer” creates elevated trapping layers in the radio refractivity structure. While direct sensing techniques provide good data, they are limited in their temporal and spatial scope. There is a need for assessing the three-dimensional (3-D) time-varying refractivity structure. Previously published results indicate that matched-field processing methods hold promise for remotely sensing the refractive profile structure between an emitter and receive array. This paper is aimed at precisely quantifying the performance one can expect with matched-field processing methods for remote sensing of the refractivity structure using signal strength measurements from a single emitter to an array of radio receivers. The performance is determined via simulation and is evaluated as a function of: (1) the aperture of the receive array; (2) the refractivity profile model; and (3) the objective function used in the optimization. Refractivity profile estimation results are provided for a surface-based duct example, an elevated duct example, and a sequence of time-varying refractivity profiles. The refractivity profiles used were based on radiosonde measurements collected off the coast of southern California     

基于传声器阵列的近场宽带波束形成方法

提出了一种适合于近场宽带传声器阵列处理的空时子带波束形成新方法。该方法通过将一个空域子带阵列和时域子带多速率滤波器组合并来同时获得空域和时域两种子带系统的优点。计算机仿真比较了其与全带自适应波束形成方法的性能,结果表明该方法对干扰有较强的抑制能力,改善了宽带波束形成频域不一致问题,并且能够并行处理,为实际语音通信系统的应用提供了一种有利途径。     

基于FPGA的相控阵探测器高速信号处理电路

为了降低相控阵探测器结构的复杂度,基于现场可编程门阵列FPGA设计了五通道高速信号处理电路。采用坐标旋转数字计算机CORDIC和多相分解滤波器设计了数字下变频器,降低每个数据流的处理负担。在波达方向DOA模块中,引入改良的收缩阵列方法,实现了对数据的并行处理,缩短了空间谱的搜索时间。利用嵌入式乘法器和加法器实现了波束形成网络BFN的可编程设计,使响应速度达到了毫秒级。实验结果表明:设计的电路总延迟仅为1.242 ms,能将原始信号放大到近13 dB,方向角测量误差小于1°,实现了对无线电基带信号的高速处理。     

基于子带化的宽带数字波束形成延时补偿新方法

采用宽带信号的相控阵雷达可获得高的距离分辨率,但也面临挑战:宽带数字波束合成和自适应抗干扰。典型的宽带自适应数字波束合成架构中,首先,在基带采用分数延时滤波器实现多通道的延时补偿;然后,将宽带信号分解为许多子带,在每个子带内做传统的窄带自适应数字波束合成;最后,合成为宽带波束输出。该信号处理方法,在宽带条件下,通过宽带延时补偿实现了精确的波束指向,取得了较好的抗干扰性能。文中基于子带化方法,提出了一种新的架构,将延时补偿合并到窄带波束合成中,即用窄带的附加相移,代替了原有的多通道延时补偿单元。结果是该架构中不再需要分数延时滤波器,大大降低了计算量节约硬件资源。同时,仍然保证了宽带阵列雷达波束的精确指向。结合相控阵雷达阵列实例,文中分别采用传统架构及所提出的新架构完成宽带波束合成,给出仿真结果以供对比,证明了新架构的有效性。     

多径环境中多用户波束形成与DOA估计

该文讨论了多径环境中多用户的波束形成与DOA估计问题,采用了解相关检测器来估计用户空间特征,提出了循环空间平滑算法(CSS)基于空间平滑的保持阵列权值维数不变的多用户波束形成算法,其理论依据是采样信号协方差矩阵的逆矩阵循环传递等效于对其求均值;利用了估计出的用户空间特征构造协方差矩阵进行空间平滑的高分辨DOA估计.仿真结果说明了循环空间平滑算法应用于多用户波束形成具有更优的抗干扰性能。     

一种基于粒子群算法的多目标子阵划分优化方法

为了降低硬件成本和系统的复杂度,子阵划分对于大型的相控阵雷达来说是必要的。传统的子阵划分方法主要针对信号处理的单一性能指标优化。针对多项指标优化的问题,本文提出了一种基于粒子群算法的子阵划分结构优化算法,相对于传统的方法能够同时优化多项性能指标,提高信号处理的性能。通过对线性阵列的划分做仿真,展示了粒子群算法对子阵级波束形成多项性能指标的提高。      

基于自适应拟牛顿法的CDMA天线阵列波束形成

针对于CDMA系统自适应天线阵列,提出了一种新的盲自适应MSINR(Maximum Signal-to-Interference plus noise ratio)波束形成算法.首先,将MSINR准则转化为一种新的无约束损失函数,并且从理论上分析该损失函数的性质.然后,应用自适应拟牛顿方法得到在线迭代波束形成算法.该算法无需训练序,而是利用CDMA信号自身的结构特点,结合空间处理提高了系统性能.最后,给出了仿真结果,表明算法具有较快的收敛速度和良好的动态跟踪能力.     

多径环境下阵列波达方向估计及互耦校正

在阵列信号处理的研究中,多径环境会降低接收机的定位精度,传统的多重信号分类算法的性能会大大降低,空间平滑算法能有效地进行解相干。当阵列天线存在互耦效应时,传统的空间平滑算法的测向性能会大大下降。针对多径环境下的均匀线阵,利用互耦矩阵的复对称带状的结构特点,结合空间平滑算法,提出了一种可以进行互耦校正的波达方向估计算法。该算法通过求解线性约束下的二次规划问题,利用谱峰搜索得到入射信号的DOA。数值仿真结果验证了该算法的有效性。     

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。