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- W3208454856 abstract "Aiming at the tracking problem for a moving target with multiple observation noises. An unscented Kalman filter based fusion tracking method with multi-error model (MEF-UKF) is proposed in this paper. In the proposed method, a multi-error model is constructed by considering the variation of the observation noise error. Then, the tracking trajectory is obtained by fusing the results getting from several parallel unscented Kalman filters corresponding to the multi-error model. Compared with the traditional algorithms, the proposed algorithm is more suitable for the real tracking scene and the precision of the proposed method is improved obviously. The proposed algorithm provides a new method for multi-observation weighted fusion, and the effectiveness of the proposed algorithm is verified by target tracking simulation." @default.
- W3208454856 created "2021-11-08" @default.
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- W3208454856 date "2021-08-17" @default.
- W3208454856 modified "2023-09-24" @default.
- W3208454856 title "The Unscented Kalman Filter Based Fusion Tracking Method with Multi-error Model" @default.
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- W3208454856 doi "https://doi.org/10.1109/icspcc52875.2021.9564471" @default.
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