摘要
提出了基于二进小波变换快速Ｋａｌｍａｎ滤波自适应反褶积方法．该方法对时变非平稳信号分时分频精细地进行快速Ｋａｌｍａｎ滤波自适应反褶积，比时域内的预测反褶积和时域内的快速Ｋａｌｍａｎ滤波自适应反褶积分辨率高．它抛弃了预测反褶积对信号平稳性的假设，具有明显的抗噪能力，比传统的自适应Ｋａｌｍａｎ滤波反褶积运算速度大大提高。经大量的模型及实际资料处理表明该方法具有明显的效果．该算法除了适合于处理地震信号外，也可以借鉴应用到其它类似信号的处理．
A new approach of fast Kalman filtering adaptive deconvolution is developed basing on dyadic wavelet transform It performs fast Kalman filtering adapgive deconvolution form time-varying nostationary signals in dyadic wavelet domain,therefore obtains higher resolution than convertional predictive deconvolution and fast Kalman filtering deconvolution in time domain The technique discards the assumption of stationarity for signals in predictive deconvolution,at the same it has remarkable ability of anti-jamming It can yield comparable performance with greatly reduced computational effort than converntional Kalman filtering adapgive deconvolution . A great deal of numerical simulations and practical data processing that this new technique tookstriking effect ,The approach not only suits for seismic data,but also can used for reference to another similar signal processing
出处
《信号处理》
CSCD
2000年第B12期21-26,共6页
Journal of Signal Processing
基金
国家自然科学基金
教育部优秀年轻教师基金资助项目
