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- W2941987130 abstract "Tracking a maneuvering target is an important technology. Due to complex environment and diversity of sensors, errors need to be optimized with respect to various motion states during the tracking process. In this paper, we first propose how to unify the coordinate system and data preprocessing in case of tracking using multiple sensors. We then combine fuzzy sets with a novel trace optimization method based on extended Kalman filter (EKF) with nested probabilistic-numerical linguistic information (NPN-EKFTO). We present a case study of trace optimization of an unknown maneuvering target in Sichuan province in China. We solve the case by using both the proposed method and the traditional EKF and offer comparative analysis to validate the proposed approach." @default.
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- W2941987130 date "2020-02-01" @default.
- W2941987130 modified "2023-10-18" @default.
- W2941987130 title "Tracking a Maneuvering Target by Multiple Sensors Using Extended Kalman Filter With Nested Probabilistic-Numerical Linguistic Information" @default.
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- W2941987130 doi "https://doi.org/10.1109/tfuzz.2019.2906577" @default.
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