基于期望信号功率最大化的鲁棒自适应波束形成算法研究

发布时间：2018-05-12 12:17

本文选题：自适应波束形成 + 鲁棒性　；参考：《西安电子科技大学》2015年硕士论文

【摘要】：随着阵列信号处理方法的发展,自适应波束形成技术由于其优异的性能在现代无线通信系统中得到越来越广泛的应用。经典的自适应波束形成算法在假定理想的条件下能够以较快的收敛速度,实现信号恢复、失真补偿以及干扰抑制的目标。但在实际应用中,由于外界因素的影响,如多径散射、阵元间的互耦和阵元校准误差,会使这些经典算法性能急剧下降。本文在研究自适应波束形成理论的基础上,针对非理想条件下的波束形成问题,提出了一种基于期望信号功率最大化的鲁棒自适应波束形成算法。论文围绕该算法展开论述,所包含的主要内容如下:1.在介绍阵列天线的发展历程及自适应波束形成基本原理的基础上,重点论述了衡量多天线系统波束形成技术性能的三种度量准则。由两种经典自适应波束形成算法的不足引出研究鲁棒自适应波束形成算法的必要性。2.在介绍对角加载采样协方差矩阵求逆算法以及不确定集类鲁棒自适应波束形成算法的基础上,本文提出了一种基于期望信号功率最大化的鲁棒自适应波束形成算法。该算法能够在信号无失真的约束条件下,在最小化系统输出功率的同时能够最大化期望信号功率。论文针对所建立的优化模型,提出了一种联合交替方向乘子和最速梯度下降的低复杂度算法。本文所提鲁棒算法克服了上述几种经典算法对参数选择的敏感性,在导向矢量误差较大时也能保证较好的输出性能,具有更强的鲁棒性和适应性。3.在不同失配场景中对本文所提算法进行了计算机仿真。仿真结果表明,论文所提算法对各种失配场景均具备较强的鲁棒性,性能明显优于对角加载采样协方差矩阵求逆算法和不确定集类鲁棒自适应波束形成算法,具有更高的输出信干噪比。
[Abstract]:With the development of array signal processing, adaptive beamforming technology has been widely used in modern wireless communication systems due to its excellent performance. The classical adaptive beamforming algorithm can achieve the target of signal recovery distortion compensation and interference suppression at a faster convergence rate under the assumption of ideal conditions. However, due to the influence of external factors, such as multi-path scattering, the mutual coupling between array elements and the calibration error of array elements, the performance of these classical algorithms will decline dramatically in practical applications. Based on the study of adaptive beamforming theory, a robust adaptive beamforming algorithm based on the maximum power of desired signal is proposed to solve the problem of beamforming under non-ideal conditions. The main contents of this paper are as follows: 1. Based on the introduction of the development of array antenna and the basic principle of adaptive beamforming, three metrics to measure the performance of beamforming in multi-antenna systems are discussed. From the deficiency of two classical adaptive beamforming algorithms, it is necessary to study robust adaptive beamforming algorithms. Based on the introduction of diagonally loaded sampling covariance matrix inverse algorithm and uncertain set class robust adaptive beamforming algorithm, a robust adaptive beamforming algorithm based on maximization of expected signal power is proposed in this paper. The proposed algorithm can minimize the output power of the system and maximize the desired signal power without distortion constraints. In this paper, we propose a low complexity algorithm combining alternating directional multipliers and steepest gradient descent for the established optimization model. The robust algorithm proposed in this paper overcomes the sensitivity of these classical algorithms to parameter selection, and can guarantee better output performance when the error of steering vector is large, and has stronger robustness and adaptability. The algorithm proposed in this paper is simulated in different mismatch scenarios. Simulation results show that the proposed algorithm is robust to various mismatch scenarios, and its performance is obviously superior to the diagonally loaded sampling covariance matrix inverse algorithm and the uncertain set class robust adaptive beamforming algorithm. It has higher signal-to-noise ratio.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TN911.7

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