AOA target tracking with new IMM PF algorithm

Dah Chung Chang, Meng Wei Fan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

3 引文 斯高帕斯(Scopus)

摘要

The state estimation technique based on the Kalman filter (KF) is widely used in many communication applications. The KF is only optimal for linear modeling with independent and identically distributed (i.i.d.) random variables and Gaussian noises. In some complicated problems, the system model is not unique and the measurement equation is nonlinear. The particle filter (PF) along with interacting multiple models (IMM) becomes an attractive solution. In this paper, a new particle filtering method based on IMM algorithm is proposed. The new IMMPF algorithm is developed for an angle-of-arrival (AOA) tracking problem with bearings-only measurements. Simulation results show that the IMMPF algorithm outperforms the IMM extended KF algorithm and achieves a root mean square tracking performance which is quite close to the posterior Cramer-Rao lower bound (CRLB).

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主出版物標題2014 IEEE 57th International Midwest Symposium on Circuits and Systems, MWSCAS 2014
發行者Institute of Electrical and Electronics Engineers Inc.
頁面729-732
頁數4
ISBN(電子)9781479941346, 9781479941346
DOIs
出版狀態已出版 - 23 9月 2014
事件2014 IEEE 57th International Midwest Symposium on Circuits and Systems, MWSCAS 2014 - College Station, United States
持續時間: 3 8月 20146 8月 2014

出版系列

名字Midwest Symposium on Circuits and Systems
ISSN(列印)1548-3746

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???event.eventtypes.event.conference???2014 IEEE 57th International Midwest Symposium on Circuits and Systems, MWSCAS 2014
國家/地區United States
城市College Station
期間3/08/146/08/14

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