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针对卡尔曼滤波方法存在的缺点,研究采用小波滤波方法进行驼峰测速雷达信号滤波。小波滤波的基本原理是对信号小波变换后的小波系数进行非线性处理,然后重构信号,滤除信号中的噪声。根据雷达信号的特点,初步选用Haar小波和二阶Dauhechies(db2)小波、3层分解、通用阈值和半软阈值算法,进行离线试验及分析。根据离线试验的滤波效果,确定选用二阶Daubechies(db2)小波、3层分解和半软阈值算法进行雷达信号滤波。利用离线试验选定的小波和算法,对采集的雷达信号进行实时滤波仿真,仿真结果与离线试验结果基本一致。将小波滤波方法与卡尔曼滤波方法对比可知,小波滤波能有效地滤除噪声、提高信噪比、减少均方差,滤波效果比较理想。因此,采用小波滤波方法进行驼峰测速雷达信号滤波,可以获得更准确的车速。
Aiming at the shortcomings of Kalman filtering method, wavelet filtering is used to filter the hump velocity radar signal. The basic principle of wavelet filtering is to perform nonlinear processing on the wavelet coefficients after signal wavelet transform, and then reconstruct the signal to filter out the noise in the signal. According to the characteristics of radar signals, Haar wavelet and second-order Dauhechies (db2) wavelet, three-level decomposition, universal threshold and semi-soft threshold are selected for offline testing and analysis. According to the filtering effect of off-line test, the second-order Daubechies (db2) wavelet, the third-layer decomposition and the semi-soft threshold algorithm are selected for radar signal filtering. Using the selected wavelet and algorithm of offline test, the collected radar signals are filtered and simulated in real time. The simulation results are in good agreement with the offline test results. Wavelet filtering method compared with the Kalman filter method shows that the wavelet filter can effectively filter out noise, improve signal to noise ratio, reduce the mean square error, the filtering effect is ideal. Therefore, the use of wavelet filter hump velocity radar signal filtering, you can get more accurate speed.