无线通信信号到达角跟踪算法研究

发布时间：2018-03-09 09:57

本文选题：DOA跟踪　切入点：稀疏重构　出处：《电子科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：在移动通信中,为了进一步提高系统容量和链路质量,基于空分复用的高精度的DOA跟踪成为研究热点。高精度的DOA跟踪在个人定位业务、战场移动通信、雷达、声纳、地震以及语音信号处理等领域中都得到广泛的关注。因此,高精度的DOA跟踪有非常重要的意义和广阔的应用前景。目前的高精度DOA跟踪在国内外已经出现了大量理论和技术研究,而传统的DOA跟踪方法仍存在较多限制,所以进一步提高DOA跟踪精度具有非常重要的意义。本文围绕高精度DOA跟踪算法展开研究,主要工作如下:1、首先对传统的MUSIC方法的DOA估计进行改进,使之应用于DOA跟踪,再与子空间DOA跟踪的另一种基于URV-ESPRIT方法的算法进行仿真对比分析。分析结果表明:基于MUSIC的DOA跟踪算法跟踪精度较高,但是不能跟踪相干源,且运算量大;基于URV-ESPRIT方法运算量相对较小,但同样不适用于处理相干源和运动轨迹接近的情况;2、给出了基于PASTd的DOA跟踪方法和基于FDPM方法的DOA跟踪方法的仿真对比分析。分析结果表明:基于PASTd的DOA跟踪方法跟踪精度较高、计算量小,但当目标运动轨迹较近时性能明显恶化;基于FDPM方法在处理运动轨迹较近的情况时跟踪性能会随着接近度下降;两种算法在处理信号源相干的情况时跟踪性能有所下降;3、在上述研究基础上,将压缩感知理论引入DOA跟踪中,给出了一种基于压缩感知的DOA跟踪方法,该方法对数据进行加窗和SVD处理后,在稀疏理论框架下,对DOA的变化量利用偏离网格的贝叶斯稀疏重构方法进行估计。仿真结果表明该方法比传统的基于子空间的DOA跟踪方法的精度更高、分辨率更高,且在信号源相干或者运动轨迹较近的情况下也具有良好的跟踪性能。本文在高精度DOA跟踪算法的基础上,给出传统子空间方法和基于子空间的快速跟踪算法的仿真对比分析,讨论各类方法的优势和劣势。同时给出了一种基于压缩感知的DOA跟踪方法,并通过仿真实验对比分析证明这些高精度的DOA跟踪算法研究有着重要的意义和广阔的前景。
[Abstract]:In mobile communication, in order to further improve system capacity and link quality, high precision DOA tracking based on space division multiplexing has become a research hotspot. High precision DOA tracking in personal positioning services, battlefield mobile communications, radar, sonar, Earthquake and speech signal processing have received wide attention. High precision DOA tracking has very important significance and broad application prospect. At present, there have been a lot of theoretical and technical research on high precision DOA tracking at home and abroad, but there are still many limitations in traditional DOA tracking methods. Therefore, it is very important to improve the tracking accuracy of DOA. This paper focuses on the high-precision DOA tracking algorithm. The main work is as follows: 1. Firstly, the DOA estimation of the traditional MUSIC method is improved to be applied to DOA tracking. The simulation results show that the tracking accuracy of DOA tracking algorithm based on MUSIC is high, but it can not track coherent source, and the computation is heavy. Based on the URV-ESPRIT method, the computation cost is relatively small. However, it is also not suitable to deal with the case where coherent source and motion trajectory are close to each other. The simulation analysis of DOA tracking method based on PASTd and DOA tracking method based on FDPM method is presented. The results show that the DOA tracking method based on PASTd is based on PASTd. The tracking accuracy of the method is high, The computational complexity is small, but the performance of the target is obviously deteriorated when the moving track is close to the target, and the tracking performance will decrease with the approaching degree when the FDPM method is used to deal with the near motion trajectory. The tracking performance of the two algorithms in the case of coherent signal source is degraded. On the basis of the above research, the compression sensing theory is introduced into DOA tracking, and a DOA tracking method based on compressed sensing is proposed. After windowing and SVD processing, the method is based on sparse theory. The variation of DOA is estimated by Bayesian sparse reconstruction method which deviates from the grid. The simulation results show that the proposed method has higher accuracy and higher resolution than the traditional subspace-based DOA tracking method. In this paper, based on the high precision DOA tracking algorithm, the traditional subspace method and the fast tracking algorithm based on subspace are compared with each other. This paper discusses the advantages and disadvantages of various methods, and presents a DOA tracking method based on compression sensing. The simulation results show that these high-precision DOA tracking algorithms have important significance and broad prospects.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.7

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