摘要
自适应波束形成是智能天线的关键技术,其核心是通过一些自适应波束形成算法获得天线阵列的最佳权重,并最终最后调整主瓣专注于所需信号的到达方向,以及抑制干扰信号,通过这些方式,天线可以有效接收所需信号。在实际应用中,收敛性,复杂性和鲁棒性的速度是在选择自适应波束形成算法时要考虑的主要因素。本文聚焦于最小均方(LMS)算法和样本矩阵求逆(SMI)的算法,分析了它们的性能,并在Matlab的帮助下将这两个算法应用于自适应波束形成。
Adaptive beamforming is a key technology of smart antenna, the core is to obtain the optimum weights of antanna array by some adaptive beamforming algorithms, and finally adjust the main lobe to foncs on the arriving direction of desired signal, as well as suppress the interfering signal, by these ways, the antenna can receive the interesting signal efficiently. In practical application, the speed of convergence, complexity, and robustness are the main factors to be considered when choosing a adaptive beamforming algorithm. This paper focuses on least mean squares （LMS） algorithm and sample matrix inversion （SMI） algorithm, analyzes their performance and makes these two algorithms applied to adaptive beamforming with the help of Matlab.
出处
《电子设计工程》
2013年第1期44-46,共3页
Electronic Design Engineering
