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- W2375707005 abstract "In order to solve the problem of accuracy decline caused by the linearization error in nonlinear reduced state Kalman filter,a new nonlinear adaptive reduced state Kalman filter algorithm is provided by using UT transformation to calculate the covariance of the system state error and modify adaptively the system noise covariance based on innovation,and the algorithm structure is summarized in detail.Then,the algorithm is applied in nonlinear measurement electro-optical tracking system and the performances of nonlinear adaptive reduced state Kalman filter were compared with unscented Kalman filter and nonlinear reduced state Kalman filter.The Matlab simulation results show that applying UT transformation and modifying adaptively the system noise covariance based on innovation in reduced state Kalman filter is valid,and the performance outperforms those of the unscented Kalman filter and nonlinear reduced state Kalman filter." @default.
- W2375707005 created "2016-06-24" @default.
- W2375707005 creator A5077034474 @default.
- W2375707005 date "2011-01-01" @default.
- W2375707005 modified "2023-09-27" @default.
- W2375707005 title "Nonlinear Innovation Adaptive Kalman Filter Algorithm for Electro-optical Tracking" @default.
- W2375707005 hasPublicationYear "2011" @default.
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