A Weighted Fusion Algorithm of Multi-sensor Based on Optimized Grouping

When measuring a certain state, multi-sensor can be divided into several groups, then processed by grouping weighted fusion algorithm. Based on the measurement equation of the state and the model of the noise, optimal weights of grouping fusion algorithm can be obtained by the principle of maximum likelihood estimation, and optimal grouping way of multi-sensor can be constructed by partheno-genetic algorithm. According to the methods mentioned above, a weighted fusion algorithm of multi-sensor based on optimized grouping is presented in the paper, which can achieve the optimal estimation of the state to be measured.