NDLI: Optimal linear unbiased filtering with polar measurements for target tracking

Content Provider	IEEE Xplore Digital Library
Author	Zhanlue Zhao Li, X.R. Jilkov, V.P. Yunmin Zhu
Copyright Year	2002
Description	Author affiliation: Dept. of Electr. Eng., New Orleans Univ., LA, USA (Zhanlue Zhao; Li, X.R.; Jilkov, V.P.)
Abstract	In tracking applications, target dynamics is usually modeled in the Cartesian coordinates, while target measurements are directly available in the original sensor coordinates. Measurement conversion is widely used such that the Kalman filter in the Cartesian coordinates can be applied. A number of improved measurement-conversion techniques have been proposed recently. However, they have fundamental limitations, resulting in performance degradation, as pointed out in Li and Jilkov (2001) of a recent survey. This paper proposes a recursive filter that is theoretically optimal in the sense of minimizing the mean-square error among all linear unbiased filters in the Cartesian coordinates. The proposed filter is free of the fundamental limitations of the measurement-conversion approach. Results of an approximate implementation are compared with those obtained by two state-of-the-art conversion techniques. Simulation results are provided.
Starting Page	1527
Ending Page	1534
File Size	432399
Page Count	8
File Format	PDF
ISBN	0972184414
DOI	10.1109/ICIF.2002.1020998
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-07-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Int. Soc. of Information Fusion
Subject Keyword	Nonlinear filters Filtering Target tracking Coordinate measuring machines Noise measurement Electric variables measurement Mathematics Mathematical model Degradation Maximum likelihood detection
Content Type	Text
Resource Type	Article

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