摘要
空域谱估计又称波达方向(direction of arrival,DOA)估计,是阵列信号处理领域中的一项重要内容,其任务是估计空间某一区域内感兴趣信号的到达方向。近年来空域谱估计理论日趋成熟,论述了Bartlett、Capon和多重信号分类(multiple signal classification,MUSIC)算法的原理和性能。在性能分析上,对窄带空域信号的方向估计进行MATLAB仿真,比较上述3种算法的分辨率,实验结果表明MUSIC算法分辨率最高,Capon次之,增加阵元数可提高算法分辨率;为使算法能有效应用到实际阵列信号处理中,还从信噪比、阵元数和快拍数这3个方面进行Monte Carlon实验对比,深入分析了其对算法测量准确度的影响,实验结果表明高信噪比情况下时测量准确度较高,改变快拍数和阵元数不会影响测量;低信噪比情况下可以通过增加阵元数和快拍数提高测量准确度。
Spatial domain spectrum estimation, also known as direction of arrival(DOA)estimation, is an important part of the field of array signal processing. Its task is to estimate the direction of arrival of signals of interest in a certain area of space. In recent years, the theory of spatial domain estimation is becoming more and more mature. The principles and performance of Bartlett, capon and multiple signal classification(MUSIC) algorithms are reviewed. In the performance analysis, Matlab simulation is carried out on the direction estimation of narrow-band spatial domain signals, and the resolutions of the above three algorithms are compared. The experimental results show that the Musci algorithm has the highest resolution, and Capon is the second. Increasing the number of array elements can improve the resolution of the algorithm;The algorithm can be effectively applied to the actual array signal processing. The Monte Carlon experiment is also compared from three aspects of signal-to-noise ratio, array element number and snapshot number, and deeply analyzes its influence on the accuracy of the algorithm measurement. The experimental results show that When the signal-to-noise ratio is high, the measurement accuracy is high. Changing the number of snapshots and the number of array elements will not affect the measurement;in the case of low signal-to-noise ratio, the measurement accuracy can be improved by increasing the number of array elements and the number of snapshots.
作者
林叶枫
Lin Yefeng(Nanjing University of Science and Technology,Nanjing 210094,China)
出处
《电子测量技术》
2019年第19期101-105,共5页
Electronic Measurement Technology
