Research On Sequential Fusion Estimation Algorithms For Nonlinear Asynchronous Sampling Systems

With the rapid development of modern computer science and information technology,the research of fusion estimation technology in wireless networked multi-sensor systems(WNMSs)has received more and more attention,and it has been applied in many military and civilian fields.However,as the structure and function of multi-sensor fusion estimation systems continue to expand,it also brings a series of new problems and difficulties to the design of fusion estimator.This paper investigates the design problems of fusion estimators for nonlinear system in several cases based on sequential processing method,sensor clustering method,optimal matrix weighted fusion method and minimum mean square error criterion: one is the asynchronous sampling and transmission of sensors;the other is process noise covariance uncertainty caused by network competition and collision avoidance;the third is the fusion problems of non-synchronous local estimation.The main content can be summarized as follows.1.Aiming at the problem of asynchronous sampling and transmission of sensors in WNMSs,a hierarchical fusion estimator including nonlinear observation fusion method and sequential matrix weighting method is designed.Firstly,the sensor network is clustered,and the measurement model and the fusion time series model under the cluster sensor network are established.Then,the design process of the nonlinear fusion estimator is divided into two parts,namely the observation fusion part and the state fusion part,and the design process of them are given separately.Finally,the estimation performance of the sequential state fusion method is analyzed.2.Aiming at the uncertainty of process noise covariance in WNMSs,a nonlinear hierarchical fusion estimator under clustered sensor network is designed.Firstly,in order to solve the problem of uncertain process noise covariance,it is assumed that the process noise covariance matrix is subject to a deterministic uniform distribution.Then,a new sequential multi-cubature square root Kalman filter(SRCKF)method is proposed based the SRCKF method in the design of nonlinear measurement fusion estimator.Finally,a new sequential matrix weighted fusion method is proposed in the design of state fusion estimator.3.Aiming at the fusion estimation problem of asynchronous local estimate in WNMSs,an asynchronous matrix weighted state fusion estimation method is proposed.Firstly,an estimation model suitable for asynchronous fusion estimation system is established.Then,the square root cubature Kalman filter(SRCKF)method is used to calculate the state estimates at each sensor's sampling time over the fusion period,and the design process of the asynchronous matrix weighted fusion estimator is given based on minimizing the trace of the estimation error covariance matrix.Finally,the calculation of cross-covariance matrix between the asynchronous local estimate is given.Finally,the content of the thesis is summarized and the problems that need to be solved next are prospected.