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     

An efficient robust adaptive filtering algorithm based on parallelsubgradient projection techniques

This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The statistical noise information is quantitatively formulated as stochastic property closed convex sets by the simple design formulae developed in this paper. A simple set-theoretic inspection also leads to an important statistical reason for the sensitivity to noise of the affine projection algorithm (APA). The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces that are highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. The numerical examples show that the proposed adaptive filtering scheme realizes dramatically fast and stable convergence for highly colored excited speech like input signals in severe noise situations     

等角圆锥投影法的误差分析

在电子对抗系统对空中目标定位时,为了简化复杂的计算,在目标不太高时,常用二维坐标.本文对较为广泛被人们接受的一种地图投影方法-等角圆锥投影法的误差进行了分析,给出在不同距离内采用等角圆锥投影方法的距离误差和方向角误差,以便在实际应用中有选择使用.     

一种新颖的抗阶数过估计的增强子空间盲辨识算法

研究了子空间盲辨识算法在信道阶数过估计时失效的问题,提出一种新的鲁棒性强的增强算法。首先针对过估计模型,提出了"加权矩阵定理",理论证明通过构造一个加权矩阵来修正子空间算法,可消除阶数过估计的影响;然后,给出一种用指数序列构造近似的加权矩阵的增强算法。与子空间盲辨识算法相比,增强算法复杂度相当,对阶数过估计鲁棒性强。仿真实验验证了该算法的有效性。     

A method for robust stabilization

LetP(y,M) be a family of polynomials, depending on a controller parameter vector y in ⁿ⁺¹, defined as follows: a family of interval matrices, and y in ⁿ⁺¹, set Given an initial stabilizing controller y⁰, this paper provides a simple method to robustify y⁰, i.e., to obtain a controller parameter vector y¹ which is more robust than y⁰. Furthermore we define the stability factort for a given robustly stable controller y, which serves as a measure of the robustness of y.     

An efficient built-in self test method for robust path delay fault testing

Single Input Change (SIC) testing has been proposed for robust path delay fault testing. In this letter a new Built-In Self Test (BIST) method for SIC vector generation is presented. The proposed method compares favourably to the previously proposed methods for SIC pattern generation with respect to hardware overhead and time required for completion of the test.     

Tri-tracking method for robust object tracking

A novel tri-tracking method for tracking objects is proposed. The tracker trains three support vector machines with labelled frames, in which an object is represented using three independent feature histograms. Based on the confidence map created by each classifier, the object position is given by the mean shift. Experiments on several video sequences show the robustness and accuracy of the proposed method.     

A robust iterative method for Born inversion

We present a robust iterative method to solve the inverse scattering problem in cases where the Born approximation is valid. We formulate this linearized inverse problem in terms of the unknown material contrast and the unknown contrast sources and we solve the problem by minimizing a cost functional consisting of two terms. The first term represents the differences between the actual data and the modeled data, while the second term represents the misfit in the constitutive relations between the contrast sources and the incident fields. In each iteration, the contrast sources and the contrast are reconstructed alternatingly, using subsequently a conjugate gradient step for the contrast source updates and a direct inversion of a diagonal matrix for the contrast. A further regularization with a multiplicative regularization factor is discussed. In this regularization procedure the relative variation of the contrast is minimized as well. As a test case we consider the two-dimensional (2-D) transverse magnetic polarization problem. Synthetic numerical examples are presented in order to compare the presented algorithm to the traditional Born algorithm. Results with respect to the inversion of experimental data are presented as well. In addition, some inversion results for the subsurface sensing problem, both in two and three dimensions, are presented.     

An improved method for symbolic reliability analysis

This paper describes a method for finding the terminal-pair reliability expression of communication networks. This method incorporates bit manipulation and Boolean operations for generating a sum of disjoint products (SDP) expression in which each term has 1:1 correspondence with respective minimal path (or cut). This method is convenient and efficient. An example of the method is given.     

Illumination robust face recognition using random projection and sparse representation

Under uneven illumination, the performances degrade significantly for some existing face recognition methods. It is a challenge for face recognition methods to work effectively under different illumination conditions. In this paper, an illumination robust face recognition method, based on random projection and sparse representation, is proposed. In the proposed method, face images are preliminary illumination normalized by gamma correction and difference of Gaussian filtering, and then several projection spaces are obtained by iterative random projection, followed by constructing an initial sample space using Fisher discrimination analysis. This scheme enriches the discrimination abilities of sample features and achieves the security and completeness for biometric template. Test samples are sparsely decomposed into each subspace, and based on statistical average residual, a modified sparse representation method is proposed to realize face recognition with higher stability and illumination robustness. Experimental results indicate that the proposed method provides competitive performance with acceptable computational efficiency. Specifically, for the five subsets of Yale B database, our approach achieves 99.74% average recognition rate, which performs higher accuracy than that of comparative methods.     

采样伺服控制系统鲁棒稳定性分析方法

对新一代高性能数控机床研制的整体性性能要求是高速度、高精度、高效率和高可靠性.其关键性的基础和技术之一就是高性能采样伺服控制系统的设计.这类控制系统设计的根本问题是系统鲁棒稳定性的分析.现利用根分布判别方法,对一类具有区间扰动的采样伺服控制系统鲁棒稳定性条件进行了研究,给出了两条鲁棒稳定性判别准则.当系统闭环特征多项式系数呈区间递减性质时,系统鲁棒稳定.这两条判别准则可适用于任意采样控制系统的鲁棒稳定性分析.     

Application of Toeplitz covariance estimation to adaptivebeamforming and detection

Array processing algorithms for adaptive beamforming and the adaptive detection of radar targets in unknown interference are proposed and simulated. These algorithms rely on estimates of the interference covariance which are constrained to be Toeplitz. It is shown that the incorporation of this constraint into the covariance estimation has a significant impact on the adaptive beamformer and adaptive detector performance     

Random projection method for ultra wideband signal acquisition

High-speed high-resolution analog-to-digital(A/D) conversion demanded by ultra wideband(UWB) signal processing is a very challenging problem.This paper proposes a parallel random projection method for UWB signal acquisition.The proposed method can achieve high sampling rate,high resolution and technical feasibility of hardware implementation.In the proposed method,an analog UWB signal is projected over a set of random sign functions.Then the low-rate high-resolution analog-to-digital convertors(ADCs) are us...     

New robust threshold setting method for frequency-hopping acquisition

A new, very robust threshold setting method for the serial search acquisition of frequency hopping (FH) waveforms, the 'reference channel detector' (RCD), is proposed and analysed. It is shown that this detector has considerable immunity when subjected to large signal dynamics and pulse jamming. Especially in pulse jamming, this procedure is a much more appropriate solution than the constant and adaptive threshold setting methods reported previously.<>     

Support vector method for robust ARMA system identification

This paper presents a new approach to auto-regressive and moving average (ARMA) modeling based on the support vector method (SVM) for identification applications. A statistical analysis of the characteristics of the proposed method is carried out. An analytical relationship between residuals and SVM-ARMA coefficients allows the linking of the fundamentals of SVM with several classical system identification methods. Additionally, the effect of outliers can be cancelled. Application examples show the performance of SVM-ARMA algorithm when it is compared with other system identification methods.     

Fast feature extraction method for robust face verification

A feature extraction technique for face verification is proposed. It utilises polynomial coefficients derived from 2D discrete cosine transform (DCT) coefficients of neighbouring blocks. Experimental results suggest that the technique is more robust against illumination direction changes than 2D Gabor wavelets, 2D DCT and eigenface methods. Moreover, compared to Gabor wavelets, the proposed technique is over 80 times quicker to compute.     

An `add-on' method for the analysis of scattering from large planarstructures

A so-called add-on procedure is proposed to deal with the data analysis problem resulting from the collection of scattering data from large planar structures. The computations (involving of the order of a few thousand unknowns) is undertaken in a gradual manner by building up the body from small patches which are added sequentially. The procedure is based on an initial expansion of the unknown current distribution into subsectional (pulse-type) basic functions. Each segment of the scatterer carries an unknown amplitude which is the response to an incident wave. However, rather than forming a matrix equation for these responses, they are computed in a gradual manner where the scatterer is built up from these segments as they are added one at a time. At the end of each addition of a segment, the result for scattering from a partial body is obtained. At each stage, the problem solved reflects the size of the small addition only, and the solution to an actual partial body is obtained. An important feature of this method is its ability to utilize a priori known information on a portion of the scatterer as an initial stage for the economic analysis of the entire structure. The process takes into account the interactions between all segments of the body. The process proves to be very efficient both in terms of computation time and storage requirements, as seen in the computed examples on of the order of 1000 to 6000 unknowns     

Iterative instrumental variable method for robust identification ofsystems

A new off-line method, called the robust iterative instrumental variable method with modified residuals, is presented for robust identification of systems in this paper. It is based on Huber's minimax principle and the instrumental variable principle. Proof of convergence for the proposed method is given along with some results of simulation. Comparison with both nonrobust methods and robust methods proposed earlier shows that the proposed method provides better accuracy of estimate and speed of convergence     

快速稳健的背景运动场估计方法

从运动背景中检测与跟踪运行目标是计算机视觉研究领域的热点,其中的困难之一是消除运动背景的影响,提出一种基于均匀稀疏采样减少仿射变换参数估计计量的快速方法,并且利用Huber函数对误差的敏感度不同的特性,使得背景的仿射参数估计过程只对背景像素点敏感,减少了前景运动物体对参数估计造成的误差,提高参数估计的精度。     

An efficient method for the electromagnetic analysis of slotted-waveguide antenna arrays

A rigorous method for the analysis of a broad class of multielement slotted-waveguide antenna arrays is described. The original electromagnetic problem is reduced to a system of integrodifferential equations, which is efficiently solved on the basis of the Galerkin method with consideration for the edge singularity of the electromagnetic field. The basis functions are the weighted Chebyshev polynomials of the first and second kinds. The accuracy of the obtained results is confirmed via comparison with available experimental and theoretical results. Features of the frequency characteristics of nonresonant arrays are analyzed.