- 期刊
- OpenAccess
Amended Kalman Filtering with Intermittent Measurements in Target Tracking
摘要
This paper focuses on the state estimation problem of target tracking with intermittent measurements. Leveraged by the posterior measurements, an amended Kalman filter is proposed in this paper to improve the precision of the current estimated state. Both the deduction and proof of the amended Kalman filter are discussed specifically to distinguish amended Kalman filter from the Kalman smoother. Extensive simulations are conducted and the simulation results verify the excellent tracking performance of the amended Kalman filter.
延伸閱讀
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- 張瀚元（2019）。Kalman Filter Based Visual Inertial Target Pose Estimation with Sensor-to-sensor Self Calibration〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU201902155
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