共轭梯度自适应波束形成算法

本文讨论了共轭梯度算法在自适应波束形成中的应用，指出在时域和空域同时处理，与仅在时域或空域处理的方法相比，不仅在性能上得到了改进，而且放宽了对阵元数目的要求。同时提出了一种前后向平均和多层前后向处理的结构和方法，使算法在上得到了进一步的改善。     

基于时域和空域混合的低信噪比视频降噪算法及其分析

论述了几种基于时域和空域混合的对低信噪比视频图像进行降噪处理的算法.考虑单独使用时域或空域降噪算法对视频图像进行处理的缺点和不足.在时域上,由于视频图像帧与帧之间有较强的相关性,采用递归加权算法;在空域上,分别采用第二代Curvelet变换理论的Wrap算法( Wrapping-Based Transform)、全变差...     

基于时空二维目标描述的红外小目标跟踪

根据红外弱小目标的时空域特性,提出了一种基于时空二维直方图均值移动的红外弱小目标跟踪方法。本文构建了空域分量和时域分量来表示红外弱小目标,形成时空二维图像。当前帧图像包含目标的空域分布信息,因此将当前帧图像作为空域分量;差分图像包含目标的运动特性,反映了目标的时域特性,因此将前后两帧差分图像作为时域分量。利用时空二维目标表示方法,采用均值移动算法进行目标跟踪,同时根据Bhattacharyya系数来更新目标模板。采用实际拍摄的小目标视频来检测本算法,仿真结果显示本算法能稳健的跟踪红外弱小目标,均值移动算法的跟踪精度得到了较大的提高。     

H.263编码视频流的混合错误掩盖

当H．263编码视频流在因特网上传输时，易受错误的影响，错误不但会影响当前帧还会继续扩散到以后的解码帧，从而导致图像质量的严重恶化，目前消除错误影响的常用算法是空域掩盖和时域掩盖算法，但是单纯地使用空域算法会造成图像的钝化，而时域算法则无法处理大运动的图像区域，因此，建议了一种时域和空域混合掩盖算法，同时使用两类算法对发生错误的图像帧进行掩盖。模拟结果显示该算法能够达到可以接受的图像质量，适应于视频会议、远程教育等应用的要求。     

基于时延分数阶相关函数时空处理的子空间测向算法

本文定义了一种时延分数阶相关函数和阵列输出信号的时延分数阶相关矩阵,在此基础上,提出了一种新的基于时延分数阶相关函数时空处理的了空间测向算法一时延分数阶相关MUSIC(TLFOC-MUSIC)算法。该算法在进行空域处理的同时,引入了时域处理,弥补了空域信息的不足,更充分地开发了空间信号中的有用信息,提高了算法的稳健性和测向的性能,对SαS噪声和干扰有较强的抑制作用。计算机仿真实验结果验证了该算法的有效性和稳健性。     

机载相控阵雷达近程杂波抑制的俯仰向空域自适应算法

该文针对机载平面阵列相控阵雷达的动目标检测提出了一种俯仰向空域自适应的近程杂波抑制算法。该方法利用平面阵列天线在俯仰向的自由度,在近程杂波的支撑区域内沿着多普勒单元选取训练样本估计协方差矩阵,计算俯仰向空域最优权。在存在距离模糊的情况下,该方法可以自适应地滤除近程杂波,保留远程杂波,从而增强了杂波的距离均匀性,有利于提高后续的方位空域和时域STAP的性能。     

一种提升电视图像质量的自适应去隔行算法

提出了一种用于提升电视图像质量的自适应去隔行算法。该算法中,待重建像素先分别在时域与空域进行重建,然后综合处理得到最终的重建值。空域滤波部分采用基于边缘自适应的方法,能较理想地解决运动图像的边缘锯齿等效应;时域滤波部分则基于运动自适应的方法,有效地提高了运动检测的准确性。测试结果表明,该算法实现较简单,且能有效改善去隔行后的电视图像质量。     

基于时空预测的H.264快速帧内预测模式选择算法

提出了一种基于时空预测的H.264快速帧内预测模式选择算法,算法充分利用视频序列中的空域和时域上的相关性,通过构建空域和时域的最佳帧内模式概率直方图来改进Pan等人提出的基于边缘方向直方图的帧内快速模式选择算法.实验结果表明,基于时空预测的H.264快速帧内预测模式选择算法在保持基本相同的编码图像质量和输出码率的同时,可显著减少编码时间,显著提升H.264的编码性能.     

结合时空梯度感知特征的HEVC-SCC码率控制算法

针对屏幕内容视频具有大量文字、图形区域以及锐利边缘的特点，本文在HEVC-SCC编码标准上提出一种结合时空梯度感知特征的HEVC-SCC码率控制算法。考虑把有效的码率用在对于人眼视觉系统更加敏感的特性上，本算法主要从空域和时域两方面进行屏幕内容视频感知特性的提取。在空域方面，采用差分算子提取梯度幅值信息，得到空域特征的描述子；在时域方面，采用可以较好描述屏幕内容视频感知特征的梯度相似性度量信息，结合相邻帧间的相关性，得到时域特征的描述子。将时空梯度感知特性进行融合，用以控制屏幕内容视频编码的码率。实验结果表明，在随机接入模式下，本算法和原始HEVC-SCC算法相比，在略微降低误码率、节省码率开销的同时提高了视频的感知质量。      

基于视觉认知机理的复杂动态背景下目标提取

针对现有复杂动态背景下目标检测与提取算法存在的局限性,提出构建一种基于视觉认知机理的时空域特征交互模式,以及基于该模式的复杂动态背景下的目标检测与提取算法。该算法通过时域特征在相似空域特征上的传递和空域特征依据时域特征一致性进行捆绑两个交互作用,实现复杂动态背景下的目标检测和提取。实验结果表明该算法不仅有效克服了传统目标检测与提取算法凭借单一特征或特征组合进行复杂背景中目标提取的不稳定性,同时大大降低了虚警率。     

DOA estimation for monostatic MIMO radar based on unitary root-MUSIC

Direction of arrival (DOA) estimation is an important issue for monostatic MIMO radar. A DOA estimation method for monostatic MIMO radar based on unitary root-MUSIC is presented in this article. In the presented method, a reduced-dimension matrix is first utilised to transform the high dimension of received signal data into low dimension one. Then, a low-dimension real-value covariance matrix is obtained by forward–backward (FB) averaging and unitary transformation. The DOA of targets can be achieved by unitary root-MUSIC. Due to the FB averaging of received signal data and the eigendecomposition of the real-valued matrix covariance, the proposed method owns better angle estimation performance and lower computational complexity. The simulation results of the proposed method are presented and the performances are investigated and discussed.     

Efficient direction-finding methods employing forward/backwardaveraging

In this paper, we develop a general approach for reducing the computational complexity of any direction finding method implemented with forward/backward (FB) averaging. We develop simplified FB data matrices in a manner paralleling previous work related to centrohermitian (correlation) matrices. Based on these simplified data matrices, efficient construction and updating of the FB correlation matrix is developed. In addition, efficient FB FFT, FB beamspace, FB EVD updating, FB SVD, and FB SVD updating methods are derived. In most cases, FB-based direction-finding methods can be simplified so that the computational complexity is reduced below that of an analogous forward only implementation. Thus, effectively twice the amount of data is processed with less total computation     

Bias correction and forward-backward averaging in frequency/DOA tracking problems

In this paper, we discuss some issues relevant to frequency and direction of arrival (DOA) tracking problems. First, we develop a linear Frequency Modulated (FM) signal model for accurately describing windowed, slowly time varying narrowband signals that typically occur in tracking problems. We then derive first order bias expressions for the peak locations of a Discrete Time Fourier Transform (DTFT) spectrum of a windowed, slowly time varying linear FM signal. We also show that Forward-Backward (FB) averaging is generally inappropriate for nonstationary data, but that it is appropriate when applied to tracking the frequencies of windowed, slowly time varying narrowband signals. A major motivation for using FB averaging is to increase the efficiency of subspace based frequency/DOA estimation in tracking problems. Finally, simulations confirm our first order bias expressions, and show that FB averaging does not significantly alter (or degrade) the time varying MUSIC based frequency estimation performance over that of Forward only averaging.This research was supported in part by the National Science Foundation Grant MIP-9203296 and Texas Advanced Research Program Grant 009741-022 and 009741-065.     

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。     

基于迭代梯度方法的线性约束稳健Capon波束形成快速算法

为了缩减线性约束稳健自适应波束形成算法的计算量,使之能够应用于单快拍更新的实时信号处理应用场景,本文提出了一种基于单快拍更新和迭代梯度方法的线性约束稳健Capon波束形成快速算法,将原始算法的O(M3)时间复杂度优化到O(M2)级别。该算法使用秩1更新维护算法所需的逆矩阵并计算波束加权值的线性约束部分,使用迭代梯度方法更新波束加权值的自适应部分,将两部分按照约束缩放后相加得到波束加权值。数值仿真表明该算法收敛快速,与原始算法有着几乎相同的性能。      

Application of orthogonal perturbation sequences to adaptive beamforming

The application of orthogonal perturbation sequences to adaptive beamforming is considered. The perturbation approach is relevant when all the array element signals in an array are not accessible but the array weights are independently adjustable. The perturbation sequences can be used to provide an estimate of the gradient required for adaptive beamforming. A unified analysis of the performance of orthogonal perturbation sequences is presented, and the performance of some specific sequences is investigated. It is demonstrated that for time multiplex perturbation sequences the penality incurred because of the use of perturbations for gradient estimation in adpative beamforming is an increase by a factorNin the system time constants.     

An improved adaptive constrained constant modulus reduced-rank algorithm with sparse updates for beamforming

In this work, we propose an adaptive set-membership (SM) reduced-rank filtering algorithm using the constrained constant modulus criterion for beamforming. We develop a stochastic gradient type algorithm based on the concept of SM techniques for adaptive beamforming. The filter weights are updated only if the bounded constraint cannot be satisfied. We also propose a scheme of time-varying bound and incorporate parameter dependence to characterize the environment for improving the tracking performance. A detailed analysis of the proposed algorithm in terms of computational complexity and stability is carried out. Simulation results verify the analytical results and show that the proposed adaptive SM reduced-rank beamforming algorithms with a dynamic bound achieve superior performance to previously reported methods at a reduced update rate.     

Adaptive Beamformers for High-Speed Mobile Communication

In this work, we propose a fast conjugate gradient method (CGM) for beamforming, after thoroughly analyzing the performances of the least mean square (LMS), the recursive least square (RLS), and the sample matrix inversion (SMI) adaptive beamforming algorithms. Various experiments are carried out to analyze the performances of each beamformer in detail. The proposed conjugate gradient method does not use the Eigen spread of the signal correlation matrix as in the case of the LMS and the RLS methods. It computes antenna array weights orthogonally for each iteration. Hence the convergence rate and the null depths of the proposed method are much better than the LMS, the SMI the RLS and the classical CGM. Also, the simulation results confirm that this method has a speed improvement of about 60% over the classical conjugate gradient method. This aspect significantly reduces the processor burden and saves a lot of power during the beamforming process. Hence the proposed method is superior compared to the LMS, the RLS, the SMI, and classical CGM and most suitable for high-speed mobile communication.

     

一种分离小阵元数阵列信号的新方法

 小阵元数阵列在利用波束形成技术完成信号分离的任务时,受到阵元数、多径等条件的限制,性能会大幅度下降甚至失效.利用自适应对消和波束形成相结合的处理方法,通过置零点波束形成再级联自适应对消,在信号方向已知的条件下,可以大幅度提高阵列信号处理的性能,有效的进行信号分离.仿真实验证明了该方法的有效性.