DocumentCode
2780170
Title
Improving performance of radar trackers by using H∞ techniques
Author
Atiullah, Tariq
fYear
2005
fDate
17-18 Sept. 2005
Firstpage
163
Lastpage
166
Abstract
Kalman filters and extended Kalman filters are extensively used as observers in radar trackers in order to estimate the future position of the target. Kalman filters are linear filters while extended Kalman filters are non linear in nature. Extended Kalman filters therefore show better performance because A,B,C and D matrices are continuously updated. In both cases however basic LQR techniques are used to calculate the state space matrices. The aim of this paper is to design a H∞ observer by robustifing the Blackman´s state space plant model through H∞ loop shaping procedure so that it can tolerate maximum uncertainty. The paper also compares the performance of the designed observer with an extended Kalman filter in order to demonstrate the superiority of the H∞ technique.
Keywords
Kalman filters; observers; radar tracking; ∞ techniques; Blackman state space plant model; Kalman filters; extended Kalman filters; linear filters; radar trackers; Nonlinear filters; Predictive models; Radar tracking; Riccati equations; Robust control; Robustness; Stability; State-space methods; Target tracking; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies, 2005. Proceedings of the IEEE Symposium on
Print_ISBN
0-7803-9247-7
Type
conf
DOI
10.1109/ICET.2005.1558873
Filename
1558873
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