外测数据处理中小波滤波的鲁棒性算法研究

Wavelet-based Robust Filtering Algorithm for Tracking Data Processing

为消除外测数据处理中异常值和噪声信号对处理结果的影响，结合数据处理的实际，给出一种基于小波变换的鲁棒性滤波算法。首先用移动中值滤波算法剔除原始数据中的异常值，然后采用小波系数去噪算法并结合经验维纳阈值滤波算法，抑制数据中的噪声。仿真计算及实际工程应用表明，该算法在保留特征段及有用信息的同时，有效地剔除了异常值，抑制了噪声，具有很好的鲁棒性。

In order to reduce the influence of the outliers and noise in tracking data processing on the processing result, the paper puts forward the wavelet-based robust filtering algorithm of processing data combining with the fact of tracking data proeessing. It utilizes the moving median filtering algorithm to reject outliers in the original data, Then it combines wavelet de-noising method with empirical Wiener thresholding to suppress noise. Simulation calculation and real engineering application show that this novel algorithm preserves the useful information while eliminating noise and outliers. The algorithm has been proven to be reliable and robust.