【作者】 杨磊；

【导师】 杨志伟； 郭磊；

【作者基本信息】 西安电子科技大学 ， 电子与通信工程， 2014， 硕士

【摘要】 空间谱估计与自适应波束形成技术作为阵列信号处理的主要应用方向,广泛被应用于雷达、声呐和通信等领域。但是,当来波信号中存在邻近的强弱目标时,强信号会掩盖弱信号的信息,准确估计弱信号波达方向困难。此外,阵列响应误差、阵元位置误差以及期望信号出现在样本数据中等因素使得自适应波束形成算法性能下降明显。本文针对上述问题进行了研究,主要工作包括:(1)以多重信号分类(multiple signal classification,Music)算法为参考,对比分析了典型的强弱信号信源波达角(Direction of Arrival,DOA)估计算法,包括RELAX算法、干扰阻塞法以及SSMusic算法。明确了它们的适用情况和优缺点。在此基础之上,通过交换大特征值顺序构造的伪数据协方差矩阵,提出了一种基于伪信号协方差矩阵的强弱邻近信源DOA估计方法。该方法减小了对硬件的要求,实现过程简单。最后,克服了经典方法中抑制强信号时对邻近弱信号引入损失的缺点,提出了基于最大似然的强弱邻近信源DOA估计方法。理论分析与仿真实验证明了所提方法的正确性与有效性。(2)针对期望信号出现在样本数据中,出现信号相消现象以及自适应波束形成算法对阵列误差敏感的问题,研究了经典的提升自适应波束形成算法稳健性的方法,如信号特征子空间算法、对角加载算法、最差情况下性能最优算法、二次规划算法以及干扰加噪声协方差矩阵重构算法等。详细描述了这些经典方法提升自适应波束形成算法的基本思想与实现途径,并明确了这些方法的性能与适用情况,最后通过仿真实验分析了方法的有效性与优缺点。更多还原

【Abstract】 As the primary aspects of array signal processing, direction of arrival(DOA) estimation and adaptive beamforming technique are widely used through radar, sonar and communication, etc. However, the strong signal will cover the weak signal in the vicinity of strong and weak signals which makes it difficult to give the weak signal an accurate estimation. In addition, array response errors, element position errors and the fact that the desired signals may exit in the sample data will degrade the performance of adaptive beamforming algorithm obviously. This dissertation aims at the problems mentioned above. The main work can be summarized as follows:(1) Take the multiple signal classification(Music) for example, we analyze the typical DOA estimation algorithms for strong and weak signals, involving the RELAX algorithm, the jamming jam method(JJM) and SSMusic algorithm, and discuss their requirements, advantages and disadvantages. Then, reconstruct the pseudo-covariance matrix by arranging the order of eigen-values afresh and propose a new DOA estimation algorithm for strong and weak signals based on pseudo-covariance matrix. The method is simply realizable and has low demands for hardware. Finally, we propose a DOA estimation algorithm based on maximum likelihood(ML) for strong and weak signals which avoids the loss of weak signals induced by the suppression of strong signals. Theoretical analysis and simulation verify the accuracy and effectiveness of the proposed methods.(2) Aim to avoid the signal cancellation caused by presence of desired signal in sample data and resolve the problem of sensitivity to array errors for adaptive beamforming, we study on robust adaptive beamforming algorithms, such as signal eigen-subspace method, diagonal loading algorithm, worse-case based method, sequential quadratic programming method, interference-plus-noise matrix reconstruction method and so on. The dissertation describes the basic ideas and the ways of realization as well as the application conditions for the typical algorithms. Finally, we analyze the effectiveness, advantages and disadvantages through the simulations.更多还原