期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 28, 期 2, 页码 346-360出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2019.2906577
关键词
Target tracking; Linguistics; Kalman filters; Probabilistic logic; Sensor systems; Extended Kalman filter (EKF); nested probabilistic-numerical linguistic information (NPN-EKFTO); trace optimization; tracking maneuvering target
资金
- National Natural Science Foundation of China [71571123, 71771155, 71801174]
- China Scholarship Council [201706240012]
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.
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