FMCW测距雷达的信号处理技术研究与实现

发布时间：2018-03-03 12:52

本文选题：调频连续波雷达　切入点：经验模态分解　出处：《中北大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着雷达技术的迅速发展，采用调频连续波（Frequency Modulated Continuous Wave，FMCW）雷达体制的测距测速系统越来越广泛地应用于日常生活和工业生产中，并且各个领域对测量的精度要求也越来越高。由于雷达信号在传播过程会受到热噪声、地杂波等噪声的影响，会造成一定的测量误差，本文在对FMCW雷达差频信号特点和造成FMCW雷达测量误差原因分析的基础上，提出了一种综合的信号处理算法。该算法首先通过自适应的降噪方法对差频信号进行预处理，然后运用基于快速傅里叶变换（FastFourier Transformation，FFT）的频率估计算法精确地估计出差频信号的频率，最后根据距离公式实现对目标信息的提取。论文首先介绍了FMCW雷达系统典型的结构框图和三角波调制方式下的FMCW雷达测距测速的基本原理，并分析了造成FMCW雷达测量误差的原因；其次根据差频信号的特点，提出了自相关检测法和基于经验模态分解（Empirical Mode Decomposition，EMD）的降噪算法，这两种方法都可以自适应地提取出淹没在噪声中的微弱差频信号，来提高信噪比；然后针对采用快速傅里叶变换对差频信号进行频谱分析时存在栏栅现象和能量泄露的问题，介绍了比值法和能量重心法这两类常用的频谱校正理论，并在比值法的基础上提出了基于FFT系数的频率估计算法，避免了求信号幅度谱的复数求模运算，在能量重心法的基础上提出了结合调整频偏或截断长度的能量重心法，进一步提高了差频信号的频率估计精度。最后借助于FMCW雷达收发器IVS-163和MP424数据采集卡，开发了基于LabVIEW的FMCW雷达测距系统，可对差频信号进行实时的采集和处理，能够较高精度地提取目标距离信息；通过整体测试与试验，，验证了综合的信号处理算法的可靠性和有效性。
[Abstract]:With the rapid development of radar technology, the ranging and velocimetry system based on frequency-modulated continuous frequency Modulated Continuous wave radar system is more and more widely used in daily life and industrial production. Because radar signal is affected by thermal noise, ground clutter and other noises, the measurement error will be caused. Based on the analysis of the characteristics of FMCW radar differential frequency signals and the causes of FMCW radar measurement errors, a comprehensive signal processing algorithm is proposed in this paper. Firstly, the differential frequency signals are preprocessed by adaptive de-noising method. Then the frequency estimation algorithm based on Fast Fourier transform (FFT) is used to estimate the frequency of the travel frequency signal accurately. Finally, the target information is extracted according to the distance formula. This paper first introduces the typical structure block diagram of FMCW radar system and the basic principle of FMCW radar ranging and velocimetry under triangle wave modulation, and analyzes the causes of the measurement error of FMCW radar, secondly, according to the characteristics of differential frequency signal, An autocorrelation detection method and an empirical Mode decomposition (EMD) based noise reduction algorithm are proposed. Both of these two methods can adaptively extract weak differential signals submerged in noise to improve signal-to-noise ratio (SNR). Then, aiming at the problems of fence phenomenon and energy leakage in the frequency spectrum analysis of differential frequency signal using fast Fourier transform, this paper introduces two kinds of common spectrum correction theories: ratio method and energy center of gravity method. On the basis of ratio method, a frequency estimation algorithm based on FFT coefficient is put forward, which avoids complex modulus calculation of signal amplitude spectrum. On the basis of energy center of gravity method, an energy center of gravity method combined with adjusting frequency offset or truncating length is proposed. The frequency estimation accuracy of the difference frequency signal is further improved. Finally, with the aid of FMCW radar transceiver IVS-163 and MP424 data acquisition card, the FMCW radar ranging system based on LabVIEW is developed, which can collect and process the differential frequency signal in real time, and can extract the target distance information with high accuracy. The reliability and validity of the integrated signal processing algorithm are verified by the whole test and experiment.
【学位授予单位】：中北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

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