基于信道化结构的LFMCW雷达信号处理研究

发布时间：2018-06-23 16:15

本文选题：线性调频连续波雷达 + 距离速度去耦合　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：线性调频连续波(LFMCW)雷达通过对连续波进行频率调制来获取被测目标距离与速度信息。由于其具有无测距盲区、测距测速精度高、发射信号时宽带宽积大、接收灵敏度高、结构简单等优点,得到了国内外学者的重视,LFMCW雷达的理论研究、关键技术及其应用得到了迅速发展。其中,运动目标距离速度去耦合方法以及强目标背景下的弱小目标检测算法是LFMCW雷达信号处理的重要研究方向,也是本文研究的重点。本文首先研究了一种传统的基于差拍傅里叶-频域配对法的LFMCW雷达信号处理算法。由于LFMCW雷达在发射单一调频斜率的连续波时被测动目标差拍信号频率会出现偏移,导致无法获取准确的目标信息。因此该方法中雷达发射信号采用三角波形调制连续波,根据运动目标差拍频率在对称三角形调频连续波正、负斜率频段会出现对称偏移的特点,采用差拍傅里叶-频域配对法对目标回波进行处理,将同一个目标在正、负斜率扫频段的两个频谱进行配对,消除运动目标多普勒频率的影响,得到被测目标的真实距离与速度。该方法的优点是结构简单,易于实现,但在检测具有大动态范围的多目标差拍信号时,容易出现弱小目标无法被检测的情况。鉴于差拍傅里叶-频域配对法存在的问题,本文提出了一种基于信道化结构的LFMCW雷达信号处理新方法。该方法采用信道化结构替代传统的差拍傅里叶方法,对不同目标差拍信号频率进行检测后完成配对,实现动目标的距离速度去耦合。针对差拍傅里叶方法在检测大动态范围的多目标差拍信号时出现丢失弱小目标的问题,本文设计了高阻带衰减的原型滤波器,利用信道化结构完成强目标背景下弱小目标的检测。文中最后利用MATLAB仿真验证了基于信道化结构LFMCW雷达信号处理方法的有效性,并与传统的基于差拍傅里叶结构方法在检测弱小目标问题上进行了对比,仿真结果表明在多目标环境下,本文提出的方法可以准确测出各目标的距离、速度。当原型低通滤波器阻带衰减满足要求时,该方法可以用于弱小目标的检测,并达到较好的效果。
[Abstract]:The linear frequency modulated continuous wave (LFMCW) radar can obtain the range and velocity information of the target by frequency modulation of the continuous wave. Because of its advantages such as no blind area of ranging, high accuracy of ranging and velocity measurement, large wide band product when transmitting signal, high sensitivity of receiving, simple structure and so on, the theoretical research of LFMCW radar has been paid more attention to by scholars at home and abroad. Key technologies and their applications have developed rapidly. Among them, the de-coupling method of moving target range velocity and the weak target detection algorithm under strong target background are the important research direction of LFMCW radar signal processing, and also the focus of this paper. In this paper, a traditional LFMCW radar signal processing algorithm based on beat Fourier transform and frequency domain pairing is studied. Because LFMCW radar is unable to obtain accurate target information because of the offset of beat signal frequency when it transmits the continuous wave with a single frequency modulation slope. Therefore, in this method, the radar transmit signal modulates the continuous wave with triangular waveform. According to the beat frequency of the moving target, the symmetrical deviation will occur in the frequency band of the symmetrical triangular FM continuous wave and the negative slope frequency band. In order to eliminate the influence of Doppler frequency of moving target, two spectra of the same target in the positive and negative slope sweep band are matched by using the beat Fourier frequency-domain pairing method to deal with the echo of the target. The real distance and velocity of the target are obtained. The advantage of this method is that it is simple in structure and easy to be realized, but it is easy to detect small and weak targets in the detection of multi-target beat signals with large dynamic range. In view of the problem of beat Fourier frequency-domain pairing, a new method of LFMCW radar signal processing based on channelized structure is proposed in this paper. This method uses channelized structure instead of the traditional beat Fourier method to detect the frequency of different target beat signals and then complete the matching to realize the distance and velocity decoupling of moving targets. In this paper, a prototype filter with high stopband attenuation is designed to solve the problem of the loss of small and weak targets in the detection of multi-target subbeat signals in large dynamic range by using the subbeat Fourier method. The weak and small targets in strong target background are detected by channelized structure. Finally, the validity of LFMCW radar signal processing method based on channelized structure is verified by MATLAB simulation. The simulation results show that the proposed method can accurately measure the distance and velocity of each target in a multi-target environment. When the stopband attenuation of the prototype low-pass filter meets the requirements, the proposed method can be used to detect small and weak targets, and a better result is achieved.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51

【参考文献】