Wavelet Transform Based Multi-Sensor Optimal Information Fusion
Cai Men · Electronics Optics & Control · 2013
The problem of multi-sensor information fusion was studied in time-frequency domain,and a new optimal criteria weighted by scalars was proposed. Wavelet transform was introduced in multi-scale signal filtering. The state vector and observed value were decomposed into multi-scale signals,and the multi-scale signals( including approximate component and details) were updated. The local sensor estimation was fused via an optimal algorithm weighted by scalars,and time-domain state estimation was obtained through inverse transformation of wavelet. The method proposed can: 1) complete multi-scale filtering for the whole multi-sensor system; 2) implement information fusion from the time domain,and improve the estimation accuracy greatly;and 3) distribute fusion weights by scalars,thus only the computation of scalar weights is required and the calculation cost is reduced obviously. The simulation shows the effectiveness of the algorithm.