Abstract: In view of the diversity of sensor data, we proposed an improved method based on wavelet and neural network data fusion. Firstly, the sensor data was preprocessed. Secondly, wavelet and BP neural network were combined to optimize the data. Finally, the data was fused by calculating the credibility of the sensor. The experimental results of the sensor data fusion effect show that  the algorithm is stable and effective for data processing and data fusion. The degree of dispersion of the fusion result is better than that of weighted data fusion, Kalman data fusion and other methods.

Key words: multi-sensor, data fusion, credibility, wavelet neural network