Fusion filtering method based on pseudo-measurement model library for multisensor systems with delay measurements

摘要

Information transferring process in sensor network will appear delay, out-of-sequence even dropout. How to make full use of such information is extremely important to improve the state estimation accuracy. In this paper, it presents a new method, which can effectively improve the estimation accuracy. Firstly, a local pseudo-measurement model library is established to deal with the measurement with several steps delay, then sent the local estimates to the fusion center; Secondly, in the fusion center, under the unbiased linear minimum variances weighting fused rule, the fusion Kalman filter based on a matrix weighted fusion algorithm processes the local estimates, thus obtain the global results. Simulations verify the effectiveness of this method.