多径传播条件下宽带线性调频信号波达方向估计方法

针对信号出现多径传播情况时现有宽带信号波达方向（direction of arrival, DOA）估计方法性能下降的问题,提出了一种多径传播条件下宽带线性调频（chirp）信号波达方向估计方法,该方法将导向有效投影（steered effective projection, STEP）技术与宽带线性调频信号的时频特性相结合,对具有不同时频特性的信号分量进行分离,逐个处理,并以时频分布矩阵代替传统的协方差矩阵,从而构造有效噪声子空间,实现时域角度估计。本方法无需进行信号聚焦操作,因此理论上不受聚焦误差的影响。仿真结果验证了所提方法的有效性。      

DOA estimation with double L-shaped array based on Hadamard product and joint diagonalization in the presence of sensor gain-phase errors

A method with double L-shaped array for direction-of-arrival (DOA) estimation in the presence of sensor gain-phase errors is presented. The reason for choosing double L-shaped array is that the shared elements between sub-arrays are the most and rotation invariant property can be applied for this array. The proposed method is introduced as follows. (1) If the number of signal is one, first the gain errors are estimated and removed with the diagonal of the covariance matrix of the array output. Then the array is rotated by an unknown angle and DOA can be estimated with the relationship between signal subspace and steering vector of signal. (2) If signals are more than one, the method for eliminating gain errors is the same with the previous case, and then the phase errors are removed by the Hadamard product of the (cross) covariance matrix and its conjugate. After the errors are eliminated, the DOAs can be estimated by rotation invariant property and orthogonal joint diagonalization for the Hadamard product. This method requires neither calibrated sources nor multidimensional parameter search, and its performance is independent of the phase errors. Simulation results demonstrate the effectiveness of the proposed method.

     

“北斗”信号重构的导向矢量实时校正

针对导航应用中阵列天线导向矢量误差导致波束合成器性能恶化甚至失效的问题,提出了一种“北斗”信号重构的导向矢量实时校正算法。该算法利用重构的本地“北斗”参考信号与阵列天线接收信号进行相关解扩处理,然后利用信号子空间与信号正交补空间正交的特性,构造代价函数对各卫星方向的阵列导向矢量进行校正。仿真结果表明,经过校正的导向矢量相位误差从-100°~100°降低到-10°~10°范围内,幅度误差从-10~10 dB降低到-4~2 dB范围内;另外,导向矢量校正后,卫星信号波达方向估计误差在0.2°以内,估计精度大大提高。     

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。     

基于指向最小误差的宽带稳健波束形成方法

宽带自适应波束形成方法较常规延时求和波束形成方法具备更好的空间分辨能力和干扰抑制能力,但在实际应用中由于阵列误差和指向误差影响导致性能下降。文中在宽带指向最小误差(STMV)方法和窄带稳健Capon(RCB)方法基础上,提出了一种基于椭圆不确定集的宽带稳健波束形成方法。通过仿真验证分析了算法在强副瓣干扰和指向误差条件下弱目标检测能力;在幅频响应误差影响条件下的保持弱信号功率输出能力;并验证算法对快拍数要求低于STMV 方法。     

Robust adaptive array beamforming under steering vector errors

This paper considers adaptive array beamforming in the presence of random steering vector errors. We first formulate the problem of finding an optimal steering vector as an optimization problem. The cost function to be minimized consists of two terms which utilize a posteriori information due to the received signal data and a priori information due to the probabilistic distribution of steering errors, respectively. Two methods are then presented to find the optimal steering constraint vector. It is shown that each method yields a closed-form optimal solution if the steering error vector is an additive Gaussian random vector. We also investigate the performance for each method. Modification of the proposed methods and an implementation algorithm for dealing with the case of steering vector errors due to phase perturbation are also presented. Finally, several computer simulation examples are presented for illustration     

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     

A projection approach for robust adaptive beamforming

It is well known that calibration errors can seriously degrade performance in adaptive arrays, particularly when the input signal-to-noise ratio is large. The effect is caused by the perturbation of the presumed steering vector from its optimal value. Although it is not as widely known, similar degradation occurs in sampled matrix inversion processing when the covariance matrix is estimated while the desired signal is present in the snapshot data. Under these conditions, performance loss is due to errors in the estimated covariance matrix and occurs even when the steering vector is known exactly. In the paper, a new method based of modification of the steering vector is proposed to overcome both the problems of perturbation and of sample covariance errors. The method involves projection of the presumed steering vector onto the observed signal-plus-interference subspace. An analysis is also presented illustrating that the sample covariance errors can be viewed as a particular type of perturbation error and a simple approximation is derived for the expected beamformer performance as a function of the number of data snapshots. Both analytical and experimental results are presented that illustrate the advantages of the proposed method     

Sidelobe suppression considerations in the design of an electronically steered IFF antenna

This paper deals with considerations in the design of an electronically steered IFF antenna which is to provide sidelobe suppression through the use of a difference beam with gain higher than that of the sum beam everywhere outside of the mainlobe region. The influence of the suppression requirement upon illumination design tradeoffs in beamwidth, sidelobe levels, and taper efficiency is demonstrated theoretically for an array restricted to 16 elements. The sidelobe suppression performance for this array, with appropriate choices for amplitude taper, number of phase shifter bits and randomizing phase function, is examined in detail for susceptibility to failures in elements, failures in individual phase shifter bits, and random phase and amplitude illumination errors. In the case of random errors, performance variability with steering direction is examined and a criterion involving the radiation patterns at both the transmit and receive RF frequencies is defined as a measure of performance. It is seen that the design analyzed is successful in reducing the corresponding performance degradation to very low levels in even the worst cases. Expressions are presented for estimating the effects of increasing the number of elements upon improvements in performance in the presence of component failures or random errors.     

阵列误差下的波达方向估计

由于阵列误差的存在会降低波达角的估计精度,重点研究了迭代求解混合范数约束下的稀疏谱以提高估计精度。考虑一维线性阵列,首先建立了统一的优化函数,高精度地估计信号子空间;然后推导了误差矩阵向量化的方法,简化求解耦合误差和幅相误差的过程;最后推导了Khatri-Rao积下的扩展正交导向矢量,根据优化函数迭代求解空间谱估计。对比不同方法估计参数的均方根误差表明,通过设计优化函数迭代求解阵列误差、波达角等参数的精度较之现有方法有一定的提高。     

A DBF self-beam steering array antenna for mobile satelliteapplications using beam-space maximal-ratio combination

This paper proposes a diversity-receiving array antenna scheme achieved by digital beamforming (DBF) for the purpose of self-beam steering toward the unknown direction-of-arrival (DOA) of a modulated signal in a mobile satellite communications environment. This scheme uses a multibeam former with a spatial fast Fourier transform (FFT) for the received baseband signals to coarsely acquire the attenuated signal. It also uses a self-phasing processor (SPP) applied to the multibeam outputs for precise acquisition and tracking. In the SPP, maximal-ratio combining is achieved with simple digital numerical operations in the complex baseband, allowing for rapidity and stability in beamforming. As a result, the array antenna steers its receiving beam toward the DOA automatically without the need for nonlinear optimization methods. Moreover, the beam is steered toward the DOA of multipath signals according to their signal levels, leading to the optimal cophase recombination of all correlated signals, which improves the quality of the total receiving signal. This paper discusses the scheme, and its performance is evaluated by computational simulation and experiments conducted in a radio anechoic chamber     

基于协方差矩阵重构和导向矢量估计的稳健自适应波束形成

实际应用中, 当假定的与真实的期望信号导向矢量之间存在一定误差时, 波束形成器的性能会急剧下降, 特别是当期望信号功率很强的时候.为解决这个问题, 提出了一种新的算法.当信源数小于阵元数时, 干扰加噪声协方差矩阵具有稀疏性.新方法首先利用该特性重构干扰加噪声协方差矩阵并由此得到与干扰导向矢量正交的子空间, 使接收的数据通过该子空间得到只含有期望信号和噪声的混合信号, 然后,对该混合信号基于最大化输出功率原理估计期望信号导向矢量, 最后,把得到的导向矢量和正交子空间来构造阵列加权值.仿真结果表明:该算法分别在假定的期望信号导向矢量存在误差、期望信号很强和低快拍数时仍然具有良好的性能.     

Robust Adaptive Microphone Array with Mainlobe and Response Ripple Control

Many existing adaptive beamformers possess robustness against arbitrary array steering vector (ASV) mismatches within presumed uncertainty set. However, when the array facing a large steering direction error, their performance degrade significantly since the uncertainty in steering direction generally gives rise to an outstanding mismatch in ASV. In the applications of microphone array, large steering direction error is often unavoidable because of the motion of target speaker. Meanwhile, in addition to conventional adaptive beamformers, microphone array also requests a controlled frequency response to target signal. In this paper, we propose a new adaptive microphone array implemented in frequency domain with controlled mainlobe and frequency response. A compact ASV uncertainty set explicitly modelling steering direction error and the other arbitrary ASV errors is exploited to derive beamformer with robust constraints on array magnitude response. Numerical results show that the proposed microphone array not only produces large controlled robust response region and robust frequency response, but also achieves high performance in SINR enhancement.     

共形天线阵元位置误差校正的辅助阵元法

共形天线的安装和测量以及载体平台表面的变形和振动均会引起阵元位置误差,严重影响 共形天线的测向性能。通过设置４个方位未知的精确校正的辅助阵元,实现了共形天线大尺度三维 的阵元位置误差校正。给出了阵元位置误差条件下共形天线导向矢量的方位依赖的幅相误差等效 表示模型;基于子空间原理得到等效的方位依赖的幅相误差估计,进而得到共形天线阵元的三维位 置误差估计。该方法可以实现共形天线校正信源来波方位和阵元三维位置误差的联合但“去耦”估 计。计算机仿真结果验证了共形天线阵元位置误差校正的辅助阵元法的有效性     

Phased-array beam steering by multiplex sampling

One approach to phased-array antenna beam forming and steering is to multiplex the element signals into a single channel. Appropriate "sampling" of the resulting multiplexed signal can provide electronically steered and shaped beams. This paper describes four practical system concepts for linear and ring arrays based on this approach and discusses significant interrelationships between the various concepts. For linear arrays of elements, the two alternatives are to frequency or time multiplex the element signals. Frequency multiplexing of the element signals produces time-multiplexed beam output signals, and time multiplexing the element signals produces frequency-multiplexed beam output signals. It is also shown here that appropriate correlation "sampling" may be used with either of these to produce easily one or more continuously and electronically steered signal bandwidth beam outputs. Ring arrays of elements may be multiplexed and "sampled" in a somewhat analogous pair of techniques. It is also pointed out that the beam steering in this case may be visualized as the linear phase steering of a set of linear phase modes into which the signal received at the array may be resolved. Ring array beam forming and steering may thus be directly understood in terms of the previous linear array techniques.     

An alternative approach to linearly constrained adaptive beamforming

A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors. The structure is designed for use with arrays which have been time-delay steered such that the desired signal of interest appears approximately in phase at the steered outputs. One major advantage of the new structure is the constraints can be implemented using simple hardware differencing amplifiers. The structure is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches. It is also particularly useful for studying the effects of steering errors on array performance. Numerical examples illustrating the performance of the structure are presented.     

2种多通道SAR/GMTI相位误差估计方法

针对多通道合成孔径雷达(SAR)和地面运动目标检测(GMTI)系统,提出了2种通道相位误差估计方法:a)利用杂波的信号特征向量与其导向矢量的线性关系直接进行通道误差估计;b)通过对回波数据进行方位重采样,然后利用杂波信号特征向量张成的空间(即信号子空间)与真实导向矢量张成的空间相同的原理进行误差估计。实验证明,2种方法均能有效地进行通道相位误差估计,并且方法 b)具有更高的估计精确度。     

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.     

存在相干信号时的最优波束形成

本文提出一种新的存在相干信号时的最优波束形成方法。该方法首先利用估计得到的期望信号和相干信号 的方向形成变换矩阵,去掉数据中的期望信号和相干信号成分，求得不相关干扰信号的子空间以及其正交子空间，然后得到期望信号和相干信号的合成导向矢量在该正交子空间中的投影矢量，并把该投影矢量作为自适应权矢量。经理论分析表明，这种方法基本上和理论上的最优方法相同。另外，该方法可以适用于任意的阵列结构，并且对期望信号和相干信号方向估计误差具有很强的稳健性。计算机仿真结果证实了本文方法的有效性。     

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.