DocumentCode :
3660294
Title :
A new parameters adaptively adjusting method of current statistical model
Author :
Yongjian Yang;Xiaoguagn Fan;Shengda Wang;Zhenfu Zhuo;Jianguo Nan;Lei Huang
Author_Institution :
Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi´an, Shannxi Province, 710038, China
fYear :
2015
Firstpage :
1738
Lastpage :
1742
Abstract :
The fixed maximum acceleration and maneuvering frequency of current statistical model leads to the divergence of filtering algorithm. In this study, a new model which employs innovation dominated subjection function to adaptively adjust maximum acceleration and maneuvering frequency is proposed based on current statistical model. Although the new model has a better performance, a fluctuant phenomenon appears. As far as this problem is concerned, a new filter algorithm which is based on amendatory and adaptively fading kalman filtering is proposed. The results of simulation indicate the effectiveness and coherent of the new model and the new algorithm, and their well performance in maneuvering target tracking.
Keywords :
"Adaptation models","Target tracking","Acceleration","Filtering algorithms","Accuracy","Filtering","Technological innovation"
Publisher :
ieee
Conference_Titel :
Information and Automation, 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICInfA.2015.7279568
Filename :
7279568
Link To Document :
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