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摘要毫米波LFMCW雷达结合了毫米波雷达和LFMCW雷达的优点，日益受到世界各国的重视。与微波雷达相比，毫米波LFMCW雷达可以实现更宽的调频带宽，获得更高的距离分辨率，即使用较小的天线，也能产生很高的角度分辨率。近年来毫米波技术的研究不断向前发展，日趋成熟，其应用领域也不断扩大，在雷达、通信、精密制导、遥感、射电天文学、医学、生物学等领域有着广泛的应用，在雷达方面尤其活跃。 PCA 是一种对数据进行分析的技术，最重要的应用是对原有数据进行简化。正如它的名字：主元分析，这种方法可以有效的找出数据中最“主要”的元素和结构，去除噪音和冗余，将原有的复杂数据降维，揭示隐藏在复杂数据背后的简单结构。它的优点是简单，而且无参数限制，可以方便的应用于各个场合。 首先阐述了毫米波线性调频雷达的研究背景和意义，然后提出了目标特征提取的困难。 第二章分析了线性调频雷达的原理，并由线性调频连续波雷达的工作原理归纳出其独特的优越性及其缺点，对雷达系统建立了等效信号与系统模型仿真模型，进行了线性调频系统的信号的 matlab仿真及线性调频测距方法的 matlab仿真。 第三章分析了主元分析的原理及特征提取方法。 实验部分对两种地面目标的仿真距离像进行了主成分提取。61015
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毕业论文关键词 毫米波 线性调频雷达 信号分析 主元分析 雷达测距 目标仿真 特征提取算法
Title Millimeter wave LFMCW radar ranging and feature extraction algorithm research
Abstract Millimeter-wave LFMCW radar combined the advantages of millimeter wave radar and LFMCW radar，being paid more increasing attention from all over the world. Compared with microwave radar, LFMCW millimeter-wave radar can achieve wider frequency bandwidth and obtain higher range resolution. Despite of using the smaller antenna, it also can produce very high angular resolution. In recent years, research on millimeter wave technology is in continuous development and becomes more and more mature, the application fields of millimeter wave technology are also expanding constantly. It is widely used in radar, communication, precision guidance, remote sensing, radio astronomy, medicine, biology, especially active in radar. PCA is a kind of data analysis technology, the most important application of this technology is to simplify data. As it's name saying: principal component analysis, this method can find the "main" elements and structure of the data effectively, remove the noise and redundancy, reduce the dimensions of original complex data, reveal the simple structure hidden behind the complex data. It has the advantages of uncomplicated, and no parameter restrictions, can be easily used in various occasions. This paper first describes the backgrounds and significance of the research on millimeter wave FMCW radar, and then put forward the difficulties of target feature extraction. The second chapter analyzes the principle of the linear frequency modulation radar, and sums up its unique advantages and disadvantages based on the linear frequency modulation continuous wave radar working principle, founds the equivalent signal and system simulation model for the radar system, performs the matlab simulation of the signal of linear frequency modulation system and matlab simulation using linear frequency modulation ranging method. The third chapter analyzes the principle and feature extraction method of principal component analysis. Experimental parts extract the simulation range image of two kinds of ground targets as the principal component extraction.
Keywords Millimeter wave Linear frequency modulated radar Signal analysis Principal component analysis Radar ranging Target simulation Feature extraction algorithm
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