Distributed consistency fusion estimation method for UAV motion information
Aiming at typical combat scenarios such as non-cooperative UAVs sneaking across the border and invading the security scene of activities,focusing on the problem of high-precision extraction of their motion information,a multi-radar detector collaborative detection strategy is adopted,and a finite time convergence collaborative detection algorithm is designed based on distributed consistency theory.Considering the various maneuvering forms of UAV targets,a tracking mathematical model of UAV targets is established under the inertial coordinate system,and discretization is proposed,and an Interactive Multi-Model(IMM)filtering algorithm and a distributed consistency-weighted fusion algorithm based on correlation criterion are proposed to achieve high-precision collaborative estimation of target motion information.In order to weaken the jitter phenomenon of IMM filter algorithm in target acceleration information estimation and the error value of acceleration estimation that is heavily dependent on the filter model and the selection of Markov probability transfer matrix,an acceleration synergy estimation strategy is further proposed based on IMM-Extended State Observer(ESO)algorithm,and a large number of mathematical simulation verifications are conducted.The results show that the proposed estimation algorithm can effectively suppress the effect of measurement noise and significantly improve the estimation accuracy of the target acceleration information.
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