Research On Weighted Measurement Fusion Estimation Algorithms For Nonlinear Systems

With the continuous enlargement of modern control system scale and the continuous improvement of system complexity,the traditional sensing devices and processing methods are far from meeting people's demands for accurate and comprehensive cognitive needs.Information fusion theory and technology come into being in this background.After decades of development,some relatively complete theories and methods are gradually formed for linear multisensory systems information fusion estimation.However,for nonlinear multisensor systems,the nonlinear multisensor systems information fusion algorithm has not been resolved because of their complexity and uncertainty.Multisensor information fusion for nonlinear systems is still a major issue and research hotspot in the field.The weighted measurement fusion estimation for nonlinear multisensor systems is studied in this paper.The main research contents are as follows:1.For nonlinear multi-sensor systems with independent noise,the mediation function is introduced so that each measurement equation can be reformed by the linear matrix and the mediation function.Then a weighted measurement fusion(WMF)algorithm is presented by using weighted least squares(WLS)method.The proposed algorithm can reduce the dimension of the measuremnt equation of the centralized fusion system,and compress the data of the centralized fusion system,and reduce the computational cost of estimation and other works.In this paper,polynomial approximate mediation functions are constructed by Taylor series,which makes the algorithm implemented.On this basis,based on the Taylor series approximation WMF algorithm and Unscented Kalman filter(UKF),a weighted measuremnt fusion UKF algorithm is designed for nonlinear Gaussian systems,and the asymptotic optimality of the algorithm is proved,that is,with the increasing of Taylor series the algorithm is asymptotically equivalent to the centralized fusion UKF algorithm.Further,based on the Taylor series approximation WMF algorithm and particle filter(PF),a weighted measurement fusion PF algorithm is also presented.This algorithm can deal with the weighted measurement fusion estimation for nonlinear multisensor systems with Gaussian or non-Gaussian noise.2.For nonlinear multisensor systems with independent noise,based on the Gauss-Hermite approximation method,another universal weighted measurement fusion algorithm is proposed.The proposed algorithm uses Gaussian function and Hermite polynomial to construct the mediation function.In this paper,in order to reduce the computational burden,a segmentation method is used to segment the state intervals and calculate the weighted coefficient matrix of each segment offline,then a database is formed.Compared with the weighted measurement fusion algorithm based on Taylor series approximation,this algorithm does not need to calculate the weighted coefficient matrix online.So it can reduce the online computational burden.At the same time,the weighted measurement fusion algorithm is used to compress and reduce the augmented high-dimensional measurements,which effectively reduces the computational complexity of the real-time estimation algorithm.Based on the Gauss-Hermite approximation WMF algorithm and UKF algorithm,the weighted measurement fusion UKF algorithm is designed.Based on the Gauss-Hermite approximation WMF algorithm and PF,a weighted measurement fusion PF algorithm is also given.3.For a nonlinear multisensor system with correlated noise,the system noise and the measurement noise are correlated at the same time stamp.First,using a decorrelation method,a nonlinear multisensor system with correlated noise are transformed into a nonlinear system with independent Gaussian noise.Then,based on the Taylor series approximation method,combined with UKF algorithms and PF algorithms,the weighted measurement fusion UKF algorithm and PF algorithm are designed.Once again,based on the Gauss-Hermite approximation method,combined with UKF algorithms and PF algorithms,the weighted measurement fusion UKF algorithm and PF algorithm are proposed.