阵列天线稳健自适应波束形成算法研究

发布时间：2018-01-12 06:09

本文关键词：阵列天线稳健自适应波束形成算法研究　出处：《哈尔滨工程大学》2014年博士论文　论文类型：学位论文

【摘要】：自适应波束形成技术是阵列信号处理的重要分支,是空间信号处理中增强期望信号,抑制干扰信号的有效方法,可广泛应用于无线通信、雷达、导航、声纳、射电天文、语音信号处理以及生物医学工程等众多国民经济及军事领域。自适应波束形成技术在理论上日趋成熟,但是在工程应用中仍面临许多实际问题。其中,实际系统中存在的各种误差,会直接影响到自适应波束形成算法在实际中的应用效果。因此如何提高自适应波束形成算法的稳健性能一直是学者研究的热点。本文主要对稳健的自适应波束形成技术进行了研究。论文的主要工作如下:针对常规Capon波束形成算法存在的问题,通过使期望信号的导向矢量在噪声子空间投影最优,提出了一种基于导向矢量不确定集约束的稳健Capon波束形成算法。算法通过对阵列协方差矩阵进行特征分解得到噪声子空间,并利用特征向量的结构特性推导出了最优对角加载量的解析表达式。针对通用信号模型下的稳健波束形成问题,提出了一种基于半正定约束的最差性能最优稳健自适应波束形成算法,通过对波束形成器进行变换,得到了一种更为简单而且易于求解的稳健自适应波束形成算法。对波束形成算法进行求解,不仅获得了自适应权矢量的近似闭式解,而且得到了一定的性能改善,并且该算法具有较低的计算复杂度。针对有限采样数据时自适应波束形成算法性能下降的问题,提出了一种基于阵列协方差矩阵估计的稳健自适应波束形成算法。该算法利用收缩方法得到一个增强的协方差矩阵估计值,替代传统的采样协方差矩阵,不需要任何参数的设定。为了克服阵列导向矢量存在误差时对波束形成器性能的影响,提出了一种基于失配误差正交分解的稳健自适应波束形成算法。利用失配误差的正交分量来修正期望信号导向矢量,同样不需要参数的设定。通过将两种算法结合,得到了一种既能改善小快拍时协方差矩阵的估计值又能克服期望信号导向矢量失配的混合稳健算法。多径环境下,为克服阵列失配误差存在时对空间平滑算法性能的影响,研究了一种基于空间平滑的稳健自适应波束形成算法。该算法基于最差性能最优准则,在保证所有可能的期望信号导向矢量和采样相关矩阵无衰减通过波束成形器的基础上,使阵列输出的干扰和噪声功率最小化。在假设事先估计得到相干干扰信号方向的条件下,提出了一种非空间平滑类的稳健自适应波束形成算法。该算法同样基于最差性能最优准则,利用期望信号约束维持对期望信号的无畸变响应,利用相干干扰信号约束在相干干扰信号方向形成零陷,同时利用最小化输出功率在不相干干扰信号方向形成零陷。为了进一步提高算法的输出信号干扰噪声比,通过相减操作将期望信号从接收信号中阻塞掉,然后利用相减之后的信号计算权矢量。基于时域宽带阵列结构,研究了一种基于幅度响应约束的稳健宽带自适应波束形成算法。该算法利用幅度响应约束可以精确的控制主瓣的波束形状,有效地解决了对信号指向误差敏感的问题。同时,算法还利用空间响应偏差约束以实现宽带频率不变波束形成,提高波束图的频率不变特性。针对空域宽带阵列结构,提出了一种基于最差性能最优的稳健宽带自适应波束形成算法,该算法同样利用空间响应偏差约束以提高宽带波束形成的频率不变性,同时为了改善算法在各种导向矢量失配下的稳健性,增加了期望信号导向矢量和空间响应偏差的不确定集约束,并且推导出了自适应权矢量的近似闭式解。
[Abstract]:Adaptive beamforming technology is an important branch of array signal processing, is expected to signal enhancement of spatial signal processing, effective method to suppress the interference signal, which can be widely used in wireless communication, radar, sonar, navigation, radio astronomy, processing of speech signal and biomedical engineering and many other national economic and military fields. The adaptive beamforming technology mature in theory, but still face many practical problems in engineering application. Among them, all kinds of errors in the system will directly affect the application of adaptive beamforming algorithm in practice. So how to improve the performance of robust adaptive beamforming algorithm has been a research hotspot. In this paper, the main technology of the research on robust adaptive beamforming. The main work of the paper is as follows: conventional Capon beamforming algorithm problems through The steering vector of the desired signal in the noise subspace projection optimization, this paper presents a robust Capon beam steering vector uncertainty set constraint algorithm based on algorithm. Based on the covariance matrix eigen decomposition to obtain the noise subspace, and the structure characteristics of the feature vector derived the analytic expression of the optimal diagonal loading factor for. Robust beamforming general signal model of the formation of problem, proposed a formation algorithm for semidefinite constraint is the worst performance of the optimal robust adaptive beam based on the beamformer transform, get a more robust adaptive beam forming algorithm is simple and easy to solve. The beamforming algorithm is used to solve the problem, not only won the closed form solution of the adaptive weight vector, and improved the performance, and the algorithm has lower computational complexity for. Limited sampling data when the adaptive beamforming algorithm is the problem of declining performance, this paper presents a robust adaptive beamforming of array covariance matrix estimation algorithm based on the algorithm. Using the contraction method obtained an enhanced covariance matrix estimation, instead of the traditional sample covariance matrix, without any parameters. In order to influence the performance of the forming device to overcome the beam array steering vector errors, proposes a mismatch error robust adaptive beam forming algorithm based on orthogonal decomposition. To correct the steering vector of the expected signal using orthogonal components mismatch error, also do not need to set parameters. By combining the two algorithms, hybrid robust algorithm has been both a to improve the small snapshot of the covariance matrix estimator can overcome the desired signal steering vector mismatch. In multipath environment, in order to overcome the loss of array The error has an effect on the performance of spatial smoothing algorithm, a robust adaptive beamforming algorithm based on spatial smoothing algorithm is studied. The worst-case performance optimization based on the criterion based on ensuring that all possible desired signal steering vector and the sample correlation matrix without attenuation through the beam forming device, the interference and noise power minimization the array output. On the assumption that the prior estimation of coherent interference signal direction conditions, proposed a robust adaptive beam forming non spatial smoothing algorithm. The algorithm is also based on the worst performance, maintaining distortionless response to the desired signal using the desired signal constraints, using coherent interference nulling in constraint coherent jamming signal direction, at the same time by minimizing the output power in the direction of the formation of coherent interference nulling. In order to further improve the algorithm. The signal interference noise ratio, through the subtraction operation the desired signal from the received signal will be blocked, and then use the signal subtraction after computing the weight vector. Time domain wideband array structure based on a robust adaptive broadband beam forming algorithm based on the constraint of amplitude response is studied. The algorithm uses the magnitude response constraints can control the main valve of the accurate the beam shape, effectively solves the problem of signal to sensitive error. At the same time, the algorithm also use spatial response deviation constraints in order to achieve broadband frequency invariant beamforming, improve the beamforming of frequency invariant characteristics. According to the spatial broadband array structure, presents a robust adaptive broadband beamforming algorithm based on the optimal performance of the worst, the the same algorithm using spatial deviation constraints to improve the frequency response invariance of broadband beamforming at the same time, in order to improve the algorithm in various direction vector The robustness of the quantity mismatch increases the uncertainty set constraint of desired signal steering vector and the spatial response bias, and deduces the approximate closed form solution of the adaptive weight vector.

【学位授予单位】：哈尔滨工程大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN911.7

【相似文献】