摘要双基地MIMO(Multiple-Input Multiple-Output)雷达的“四抗”优势使得其具有非常广阔的应用前景。其精确的目标探测能力和反隐身、反辐射、抗摧毁特性可用于检测多径杂波环境下的弱目标,对付日益先进的隐身技术和构建岸基预警雷达系统。因此,对双基地MIMO雷达的深入研究具有重大意义。28616
本文基于双基地MIMO雷达的项目背景,开展MIMO雷达的角度测量研究。首先阐述了双基地MIMO雷达的工作原理,接着仿真分析了和差比幅经典测角方法的性能,并且选择MUSIC超分辨算法与经典和差比幅算法和Capon算法的角度估计性能进行对比,归纳指出了影响测角精度的因素。最后,探讨并仿真了双基地MIMO雷达的定位精度GDOP(Geometric Dilution Precision)图。
关键词 双基地MIMO雷达,角度估计,和差波束,Capon,MUSIC,精度分析
毕业论文设计说明书外文摘要
Title Study of Super-Resolution Algorithms for MIMO Radar’s Angle Measurement
Abstract
Bistatic Multiple-Input Multiple-Output (MIMO) radar with 'four-anti' advantages possesses a broad prospect of application. The precise target detection capability and anti-stealth, anti-destroying characteristics can be used to detect weak targets under clutters, deal with increasingly advanced stealth technology and to build shore-based early warning radar system. Therefore, further study of bistatic MIMO radar is of great significance.
This paper is based on the project background of bistatic MIMO radar and mainly about the research carrying out on MIMO radar angle measurements. Firstly elaborated how the bistatic MIMO radar works, and then simulated the angle measuring performance of classical amplitude comparison of sum and difference beams. As well, the MUSIC super-resolution algorithms, sum and difference beamforming algorithms and Capon spectral estimators are selected to compare their performance on angle estimation. Moreover, the factors affecting the accuracy of angle measurements are illustrated. Finally, the positioning accuracy of bistatic MIMO radar is analyzed with GDOP maps.
Keywords bistatic MIMO radar, angle estimators, sum and difference beams, Capon, MUSIC, GDOP
目 次
1 绪论 1
1.1 研究背景和意义 1
1.2 国内外研究概况 3
1.3 本文的主要内容和章节安排 3
2 双基地MIMO雷达基本原理 5
2.1 双基地MIMO雷达几何结构 5
2.2 双基地MIMO雷达定位原理 6
3 和差波束测角 9
3.1 和差测角算法的基本原理 9
3.2 和差波束形成方法 11
3.3 仿真实验 12
4 Capon和MUSIC测角算法 15
4.1 Capon算法在MIMO雷达角度估计中的应用 15
4.2 MUSIC算法在MIMO雷达角度估计中的应用 16
4.3 仿真实验 17
4.4 超分辨算法与和差比幅算法测角的精度比较 25
5 定位精度分析 28
5.1 算法实现 28
5.2 仿真实验 29
结论 34
致谢 35
参考文献 36
1 绪论
1.1 研究背景和意义
- 上一篇:基于多测量矢量模型的压缩感知雷达时延-多普勒估计
- 下一篇:车牌识别系统中图像预处理算法的研究
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