Asynchronous Multisensor Data Fusion Algorithm based on the Decentralized Filtering Techniques

For the process of multiple sensors with different sampling rates observing the same target, an asynchronous data fusion algorithm is proposed by minimizing the track of the fusion estimation error covariance matrix in this paper. The correlation between local filters is taken into account and the computational load of the central node can be reduced by using decentralized filtering technology. The fusion period for the central node is not fixed. The simulation results for the satellite autonomous navigation system are given to demonstrate its feasibility.