飞行数据改进中值滤波和自适应小波降噪

摘要

研究飞行数据预处理时提高数据质量问题.针对飞行数据易受噪声干扰,提出了改进中值滤波和自适应小波阈值降噪的降噪算法.首先以改进的中值滤波算法对飞行数据进行处理以剔除野值;然后对剔除野值后的飞行数据进行小波分解,根据各层小波系数的噪声自相关函数确定最佳小波分解层数;最后设计了新的自适应阈值函数,对小波系数进行处理并重构,得到降噪数据.采用仿真数据和飞行数据进行实验,结果表明,改进方法取得了良好的降噪效果,改善了数据质量,证明算法有效性.%To improve the quality and reduce the noise in flight data which comes from telemetry unit,this paper presented a new flight data denoising algorithm combined with improved median filter and a new adaptive threshold shrinkage function in Wavelet Transform.Firstly,the improved median filter was carried out with the noisy signals to reject outliers.Then,the wavelet decomposition was utilized to the reject the outliers from the signals and the autocorrelation function was introduced into the detail coefficients to obtain optimal decomposition scale.Finally,a new adaptive threshold shrinkage function was employed to detail coefficients to get their results.The last denoised signals can be acquired through inverse Wavelet Transform.Simulated data and flight data were used for numerical experiments,which show that the proposed novel algorithm can better retain the original features and improve its quality.The algorithm is effective.