【作者】 杨雪；

【导师】 谢菊兰；

【作者基本信息】 电子科技大学 ， 信号与信息处理， 2018， 硕士

【摘要】 自适应波束形成技术凭借其可以自适应地调整权向量的优点,早已被应用于多个领域。在实际应用中,由于不理想因素的存在,比如信号到达角(direction of arrival,DOA)失配、导向矢量误差、快拍数过小以及样本协方差矩阵中含有期望信号成分等,导致经典的波束形成算法性能下降。近几十年来,许多稳健的波束形成算法被提出,本文重点针对均匀线阵存在未知阵元互耦以及同时存在未知阵元互耦和相干信号两种情况进行了最优稳健波束形成算法的研究。主要工作以及研究内容包括如下几个方面:1、介绍两种最优波束形成的准则,并讨论了三种经典的波束形成算法,通过仿真结果分析了算法的性能表现。2、针对期望信号存在于样本协方差矩阵中的情况,对三种基于协方差矩阵重构的算法进行了仿真研究和分析,由于这些算法同时对期望信号的导向矢量进行了重估,算法的稳健性得到了大大的提高。3、针对阵元之间存在互耦这种情况,提出了两种未知互耦信息下的最优稳健波束形成算法。利用均匀线阵的互耦矩阵的Toeplitz特性,得到包含互耦信息的信号复包络,重构出包含互耦信息的期望信号协方差矩阵和干扰加噪声协方差矩阵。最后通过分别基于输出信干噪比最大化准则以及基于功率采样的矩阵重构准则,得到稳健的波束形成。所提出的两种算法在不引入迭代过程的同时,对期望信号DOA失配、导向矢量失配以及阵元互耦都有效,输出性能十分接近最优波束形成的性能。4、相干信号的存在使数据协方差矩阵缺秩,常规的波束形成算法失去对干扰的抑制能力。而阵元之间互耦存在时,常规的相干干扰抑制方法又会失效。针对这种情况提出了未知互耦信息下的去相干干扰的稳健波束形成算法。基于一种迭代自适应方法,可以重构出去相干后的干扰加噪声协方差矩阵,最后基于最大化输出信干噪比准则,得到同时对阵元互耦以及干扰相干稳健的波束形成算法。算法在存在DOA失配时稳健,在信噪比较大变化范围内输出信干噪比都十分接近最优波束形成算法,并且收敛速度快。更多还原

【Abstract】 Adaptive beamforming has been widely used in many fields due to its advantage of adaptively adjusting the weight vector.In practical applications,the performance of classical beamformers is degraded because of many non-ideal factors,such as direction-of-arrival error,steering vector mismatch,excessive snapshots number and the exists of desired signal in the sample covariance matrix.Many robust beamforming algorithms have been proposed in recent years.This paper focuses on the optimal robust beamforming algorithm for the case of unknown mutual coupling in the uniform linear array,as well as robust adaptive beamforming of coherent signals in the presence of the unknown mutual coupling.The main work and research contents are as follows:1.Two optimal beamforming criteria are introduced.Three classical beamforming algorithms are discussed.The performance of these algorithms are analyzed through simulation results.2.For the case that the desired signal exists in the covariance matrix,three kinds of algorithms based on covariance matrix reconstruction are studied and analyzed.Because these algorithms simultaneously re-estimate the steering vector of the desired signal,the robustness of these algorithms have been greatly improved.3.In most cases,it is assumed that the array elements are independent of each other,but in practical applications,there exists mutual coupling effect due to the small spacing between the array elements.The data matrix structure is distorted.For this case,two optimal robust adaptive beamforming algorithms for unknown mutual coupling are proposed.Using the Toeplitz property of the mutual matrix of the uniform linear array,a signal complex envelope containing mutual coupling information is obtained,and the desired signal’s covariance matrix and the interference-plus-noise covariance matrix including the mutual coupling information are reconstructed.Finally,robust beamforming is obtained by using the criterion of maximizing the output signal-to-interference-plus-noise ratio and the matrix reconstruction criterion based on power sampling.The proposed two algorithms are effective for DOA mismatch,steering vector mismatch,as well as the mutual coupling without introducing any iterative process.The output performance is very close to the optimal beamforming performance.4.The existence of a coherent signals causes the data covariance matrix to be out of rank,and the conventional beamforming algorithm loses its ability to suppress interferences.Therefore,a new method based on the matrices reconstruction is proposed to deal with coherent signals in the presence of the unknown mutual coupling.Based on an iterative adaptive method,the coherent interference-plus-noise covariance matrix can be reconstructed.Finally,based on the maximum output signal-to-interference-plus-noise ratio criterion,a beamformer which is robust against mutual coupling and coherent signals is obtained.The algorithm is robust to large DOA mismatches,and the output SINR is very close to the optimal beamforming algorithm over a large range of SNR,and converges fast.更多还原