Modified wavelet transformation algorithms and its application in multi-sensor data fusion

At present, the wavelet transformation, combining with Kalman filter, is the most used algorithm in multi-sensor data fusion technology. However, wavelet transformation with Kalman filter has two aspect problems in algorithm. One aspect of the problem consists in the multi-resolution analysis (MRA) method of wavelet transformation. It only subdivides the approximate signal of low frequency band step by step effectively, which causes the precision in low frequency band being more and more high and that the detail signal of the high frequency band is invariable. Therefore MRA method has low resolving ability in frequency. The other aspect of the problem is that, some system has non-linear character in practice measuring, which makes Kalman filter precarious and even no-convergence. So the filter effect is not very good. In order to overcome the shortcoming described above, the modified multi-resolution analysis method and the wavelet domain median filter is put forward in this paper. The improved data fusion way is used to fuse multi-resolution data in the monitor of water power plantpsilas hydraulic turbine, which can fuse multi-sensors data in different resolution. The fusing result indicates the designed modified algorithm is effective.