DocumentCode :
3222145
Title :
Maneuvering Target Tracking Based on ANFIS and UKF
Author :
Zhu, Anfu ; Jing, Zhanrong ; Chen, Weijun ; Yang, Yan ; Zhang, Anxue
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
904
Lastpage :
908
Abstract :
A maneuvering target tracking algorithm is proposed to overcome the defects of poor filtering precision while using unscented Kalman filter (UKF). The method combines the merits of UKF and adaptive neuro-fuzzy inference system (ANFIS). ANFIS is used to adjust system noise covariance matrix in target tracking system. Fuzzy inference, neural networks and UKF are integrated effectively. The proposed method is applied to the simulation of radar target tracking. The simulation results show that the proposed method has advantages in higher precision, faster convergence, and stronger ability to track maneuvering targets.
Keywords :
Kalman filters; covariance matrices; fuzzy neural nets; fuzzy reasoning; radar computing; radar signal processing; radar tracking; target tracking; ANFIS; UKF; adaptive neuro-fuzzy inference system; neural networks; poor filtering precision; radar target tracking; system noise covariance matrix; target tracking maneuvering; target tracking system; unscented Kalman filter; Covariance matrix; Equations; Filtering algorithms; Fuzzy reasoning; Inference algorithms; Nonlinear filters; Radar tracking; Signal processing algorithms; State estimation; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.145
Filename :
4659619
Link To Document :
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