In this paper,we study how to design filters for nonlinear uncertain systems over sensor networks.We intoduce two Kalmantype nonlinear fitrs in centralied and dstrbute frameworks.Moreover,the tuning method for the par...In this paper,we study how to design filters for nonlinear uncertain systems over sensor networks.We intoduce two Kalmantype nonlinear fitrs in centralied and dstrbute frameworks.Moreover,the tuning method for the parameters of the filteres is established to ensure the consistency,i.e..the mean square error is upper bounded by a known parameter matrix at each time.We apply the consistent fiters to the track to-track association analysis of multi targets with uncertain dynamics.A novel track to-track asocaion algoritm is proposed to idenify whether two tracks are from the same target.It is proven that the resulting probability of mis.asociation is lower than the desired threshold.Numerical simulations on track.to track association are given to show the ffetives of the methods.展开更多
基金the National Natural Science Foundation of China(Nos.11931018,61973299)the Beijing Advanced Innovation Center for Intelligent Robots and Systems(No.2019IRS09).
文摘In this paper,we study how to design filters for nonlinear uncertain systems over sensor networks.We intoduce two Kalmantype nonlinear fitrs in centralied and dstrbute frameworks.Moreover,the tuning method for the parameters of the filteres is established to ensure the consistency,i.e..the mean square error is upper bounded by a known parameter matrix at each time.We apply the consistent fiters to the track to-track association analysis of multi targets with uncertain dynamics.A novel track to-track asocaion algoritm is proposed to idenify whether two tracks are from the same target.It is proven that the resulting probability of mis.asociation is lower than the desired threshold.Numerical simulations on track.to track association are given to show the ffetives of the methods.
