考虑互耦修正的机会阵雷达波束方向图综合优化

机会阵雷达大量天线单元在空间随机分布,波束方向图综合时考虑阵元间的互耦影响十分必要。该文基于子阵思想,提出交叉划分子阵,利用子阵的互阻抗矩阵构建任意阵的互阻抗矩阵,并结合自适应算法实现了互耦情况下的机会阵雷达的波束综合优化。该方法利用矩量法计算子阵的广义互阻抗矩阵,应用最大输出信噪比准则,在方向图区域施加干扰信号自适应地调整阵因子,综合了非均匀偶极子线阵和面阵,结果与FEKO软件仿真结果吻合良好。     

Array pattern distortion and remedies in space-time adaptiveprocessing for airborne radar

Space-time adaptive processing (STAP) for airborne early warning radar has been a very active area of research since the late 1980's. An airborne rectangular planar array antenna is usually configured into subarrays and then partial adaptive processing is applied to the outputs of these subarrays. In practice, three kinds of errors are often encountered: the array gain and phase errors existing in each element, the channel gain and phase errors, and the clutter covariance matrix estimation errors due to insufficient secondary data samples. These errors not only degrade the clutter suppression performance, but also cause the adapted array patterns to suffer much distortion (high sidelobes and distorted mainbeams), which may result in the rise of false-alarm probability and make the adaptive monopulse tracking and sidelobe blanketing more difficult. In this paper, the causes of the above three kinds of errors to array pattern distortion are discussed and a novel quadratic soft constraint factored approach is proposed to precisely control the peak sidelobe level of adapted patterns. The soft constraint factor can be determined explicitly according to the peak sidelobe level desired and the known or desired tolerant error standard deviations. Numerical results obtained by using high-fidelity simulated airborne radar clutter data are provided to illustrate the performance of the proposed approach. Although the method is presented for STAP, it can be directly applied to the conventional adaptive beamforming for rectangular planar arrays used to suppress jammers     

Blind adaptive beamforming based on generalized sidelobe canceller

The generalized sidelobe canceller (GSC) is an efficient implementation of the direction constrained adaptive array. Conventional GSC is designed according to a quiescent weight vector and a blocking matrix. The quiescent weight vector provides the array with specified array response at some direction. The blocking matrix is designed based on a priori knowledge of the direction of arrival (DOA) of the desired signal. In this paper, we propose a new GSC-based adaptive array without a priori knowledge of the DOA of the desired signal. This paper utilizes eigensubspace decomposition and statistically cyclostationary properties of the signals to design the adaptive array. A method for constructing the most efficient blocking matrix for the GSC is developed. Simulation examples illustrate the effectiveness of the proposed method.     

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.     

Adaptive antenna array using real symmetric array covariance matrix

A novel scheme using a real symmetric array covariance matrix for an adaptive antenna array in DS/CDMA is proposed. A real symmetric array covariance matrix is estimated from a complex array covariance matrix using a unitary transformation and Toeplitz matrix approximation methods. The Hermitian Toeplitzation method not only estimates a persymmetric matrix form for a real symmetric array covariance matrix but also enhances the performance of the received signal by removing the undesired effect obtained from a complex array covariance matrix. Simulation results demonstrate the effectiveness of the proposed scheme     

A robust adaptive array based on signal subspace approach

In this note, we propose a signal subspace approach that improves the performance of a beam steered adaptive array in the presence of steering errors due to look-direction error (LDE) and/or random steering error (RSE). In the method, the degrees of freedom (DOF) are reduced so as not to cancel the desired signal while preserving the optimal characteristic of the array, and thus the weights of the array are determined by a linear combination of the eigenvectors of the signal subspace. The proposed method works as far as the eigen decomposition of the input covariance matrix into signal and noise subspaces is possible. The proposed method improves noticeably the array performance of the beam steered array in the presence of steering errors and provides the optimum array performance in the absence of steering errors     

Evaluation of adaptive phased array antenna, far-field nullingperformance in the near-field region

A theory for analyzing the behavior of adaptive phased array antennas illuminated by a near-field interference test source is presented. Conventional phased array near-field focusing is used to produce an equivalent far-field antenna pattern at a range distance of one to two aperture diameters from the adaptive antenna under test. The antenna is assumed to be a linear array of isotropic receive elements. The interferer is assumed to be a bandlimited noise source radiating from an isotropic antenna. The theory is developed for both partially and fully adaptive arrays. Results are presented for the fully adaptive array case with single and multiple interferers. The results indicate that near-field and far-field adaptive nulling can be equivalent. The adaptive nulling characteristics studied in detail are the array radiation patterns, adaptive cancellation, covariance matrix eigenvalues, and adaptive array weights     

An experimental SMI adaptive antenna array simulator for weakinterfering signals

An experimental sample matrix inversion (SMI) adaptive antenna array for suppressing weak interfering signals is described. The experimental adaptive array uses a modified SMI algorithm to increase the interference suppression. In the modified SMI algorithm, the sample covariance matrix is redefined to reduce the effect of thermal noise on the weights of an adaptive array. This is accomplished by subtracting a fraction of the smallest eigenvalue of the original covariance matrix from its diagonal entries. The test results obtained using the experimental system are compared with theoretical results. The two show a good agreement     

基于旁瓣对消器的自适应零陷优化设计

现有的零陷展宽算法忽略了锥化矩阵的相位信息,在对抗强方向性、大偏差角干扰时,零陷深度变浅,干扰抑制性能严重下降。该文以虚拟空域密集干扰为切入点,推导并提出一种可用于旁瓣对消器的自适应零陷优化设计算法。该算法通过对辅助阵列数据的自协方差矩阵和主辅阵列数据的互协方差矩阵同时进行重构实现零陷区域的自适应控制,锥削矩阵只与阵元位置和展宽宽度有关,无需干扰信息,可以离线生成,不占用系统运算资源。仿真结果表明,该方法可以实现零陷区域的自适应展宽,提高非平稳干扰抑制的稳健性。     

Reactance domain MUSIC algorithm for electronically steerable parasitic array radiator

Conventional adaptive array antenna processing must observe signals on all of the array antenna elements. However, because the low-cost electronically steerable parasitic array radiator (ESPAR) antenna has only a single-port output, none of the signals on the antenna's parasitic elements can be observed. A direct application of most of the algorithms for the conventional adaptive array antenna is impractical. In this paper, A technique of estimation of direction-of-arrivals (DoAs) is proposed for the ESPAR antenna. This technique is based on the modified MUltiple SIgnal Classification (MUSIC) algorithm. The correlation matrix used in the MUSIC algorithm is estimated from the signal received through the single-port output of the ESPAR antenna as it switches over a set of antenna patterns. Simulation results show that DoAs can be estimated by the reactance domain MUSIC algorithm for ESPAR antennas. Furthermore, the statistical performance on estimation error variance of the reactance domain MUSIC estimator is analyzed and compared with the Crame/spl acute/r-Rao lower bound. Analytic and empirical results show that high-resolution DoAs estimation can be achieved by using the reactance domain MUSIC algorithm for ESPAR antennas.     

基于线性双向脉动阵列的自适应光学波前复原

针对自适应光学系统,提出了一种基于线性双向流水脉动阵列的快速波前复原方法。该方法结合直接斜率波前复原算法和线性双向脉动阵列工作特点,通过对复原矩阵进行PCT数据变换和引入资源共享,提高了阵列的单元利用率,减少了资源占用且保证了计算的实时性,同时具有阵列结构简单规整、模块性强、可扩展性好等优点。最后在FPGA上实现了61单元48子孔径自适应光学系统的波前复原,验证了方法的可行性。     

Clutter suppression for airborne phased radar with conformal arrays by least squares estimation

The radar clutter statistics for airborne conformal arrays varies by range, i.e., the clutter distributions are nonstationary, which causes performance degradation for the conventional space-time adaptive processing (STAP), which estimates the clutter covariance matrix (CCM) from data at adjacent range cells. In this paper, a novel clutter suppression method for airborne phased radar with conformal arrays is proposed that takes a form of corrected sample matrix inversion (SMI) through the CCM estimated by the least squares (LS) estimation. The estimated CCM can provide partial information about the real CCM in the novel method, which results in improved detection performance for targets in conformal array applications. Simulation results relative to several typical conformal arrays verify the effectivity of the presented method.     

迭代自适应收缩加权融合的波束形成方法

自适应数字波束形成是通过对阵列接收数据进行加权处理来获得最大的输出信干噪比,对采样协方差矩阵的依赖性较大。针对小样本条件下采样协方差矩阵求逆算法性能下降问题,提出迭代自适应加权融合样本协方差矩阵与先验协方差矩阵的波束形成算法。在估计协方差矩阵时,依据最小均方误差准则计算加权系数,并采用迭代自适应的方式更新先验协方差矩阵。仿真结果表明,所提方法能显著提高小样本条件下的协方差矩阵估计精度,能获得更大的输出信干噪比。      

Efficient eigenspace-based array signal processing using multipleshift-invariant subarrays

This paper deals with the construction of eigensubspaces for adaptive array signal processing. An efficient technique for extracting the eigensubspaces spanned by the data vector received by an N-element adaptive array is presented. We first decompose the original array into several subarrays with multiple shift invariances and find the eigensubspaces corresponding to each of the subarrays. By solving a least-squares (LS) or total least-squares (TLS) problem, the signal and noise subspaces corresponding to the original array can be found from the eigensubspaces spanned by the subarray data vectors. Hence, there is no need to perform the eigenvalue decomposition of the N×N correlation matrix of the received data vector. The proposed technique significantly reduces the required computational complexity as compared to the conventional eigenspace-based (ESB) methods. In conjunction with the spatial smoothing scheme or a proposed cross-correlation method, this technique can also deal with the case of coherent signals. The effectiveness of the proposed technique is demonstrated by several computer simulations     

On adaptive beamforming in correlated noise

This paper deals with the problem of adaptive beamforming in the presence of fully coherent (correlated) noise sources. Two different techniques are developed for minimizing the effects of coherent interference. The first method employs spatial interpolation of the array aperture, followed by spatial smoothing in order to decorrelate the desired signal and the interference. The second technique is based on a simple algebraic transformation for restoring the rank of the array signal correlation matrix, which is normally rank deficient in such situations. This technique is shown to work for nonuniform adaptive arrays as well. Extensive computer simulation results are presented to illustrate the effectiveness of the proposed techniques.This week was supported by the N.R.C., Resident Research Associateship Programme.     

Adaptive processing using a single snapshot for a nonuniformlyspaced array in the presence of mutual coupling and near-fieldscatterers

This paper presents an adaptive technique to extract the signal of interest (SOI) arriving from a known direction in the presence of strong interferers using a single snapshot of data. The antenna elements in this method can be nonuniformly spaced and there can be mutual coupling between them. In addition, near-field scatterers can also be present. First, the voltages induced in the antenna elements of the array due to interferers, mutual coupling between the elements, and near-field scatterers is preprocessed by applying a transformation matrix to these voltages through a rigorous electromagnetic analysis tool. This electromagnetic preprocessing technique transforms the voltages that are induced in a nonuniformly spaced array containing real antenna elements to a set of voltages that will be produced in a uniform linear virtual array (ULVA) containing omnidirectional isotropic point radiators. In the transformation matrix we would like to include various electromagnetic effects like mutual coupling between the antenna elements, presence of near-field scatterers and the platform effects on which the antenna array is mounted. This transformation matrix when applied to the actual measured voltages yields an equivalent set of voltages that will be induced in the ULVA. A direct data domain least squares adaptive algorithm is then applied to the processed voltages to extract the SOI in the presence of interferers. Limited numerical examples are presented to illustrate the novelty of the proposed method     

Two-Dimensional Adaptive Array Beamforming With Multiple Beam Constraints Using a Generalized Sidelobe Canceller

This paper deals with the problem of two-dimensional (2-D) adaptive array beamforming with multiple beam constraints (MBC) using a generalized sidelobe canceller (GSC). We present a method for the construction of signal blocking matrix required by the 2-D GSC. The resulting 2-D adaptive beamformer can provide almost the same performance as conventional 2-D adaptive beamformers based on a linearly constrained minimum variance (LCMV) criterion. The effectiveness of the proposed GSC is that the construction of the required signal blocking matrix requires only the computation of a few entries from analytical formulas. In comparison with conventional methods, the proposed technique gets rid of the computational complexity due to the eigendecomposition required for finding the 2-D signal blocking matrix. For dealing with the performance degradation due to coherent interference, we present a 2-D weighted spatial smoothing scheme to effectively alleviate the coherent jamming effect. Several simulation examples are provided for illustration and comparison.     

基于协方差矩阵双层重构的稳健自适应单脉冲测角

常规自适应单脉冲方法在主瓣干扰下会引起自适应波束形成性能恶化并导致其单脉冲比曲线严重失真,影响被动雷达的测角精度与跟踪性能。针对此问题,提出了一种适用于平面阵的基于协方差矩阵双层重构的稳健自适应单脉冲测角方法。首先,利用Capon功率谱通过稀疏重构法初步估计出干扰加噪声协方差矩阵,通过干扰导向矢量估计完成对协方差矩阵的优化校正以提高自适应波束形成性能;然后,基于线性约束最小方差(Linearly Constrained Minimum Variance, LCMV)准则对方位角和俯仰角进行联合线性约束以避免单脉冲比曲线在主瓣干扰下严重失真;最后,根据自适应单脉冲比值求出目标与波束指向之间的偏转角以实现目标测角。与常规方法相比,所提方法在干扰抑制能力与测角精度上都有显著提升。     

基于空时自适应处理的低空风切变风速估计方法

针对机载气象雷达在探测低空风切变时,有用信号会淹没在强杂波背景中的问题,该文提出一种基于空时自适应处理(STAP)的低空风切变风速估计方法。该方法首先利用空时插值原理校正机载前视阵地杂波的距离依赖性,获得多个独立同分布(IID)样本后估计地杂波协方差矩阵,然后构造适用于分布式低空风切变目标的空时自适应处理器,在自适应抑制地杂波的同时积累低空风切变信号,最终实现风场速度的精确估计。仿真结果表明,在高杂噪比、低信噪比的情况下,该方法可有效地自适应抑制地杂波并精确地估计风场速度。     

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