NDLI: Detecting track-loss for the Probabilistic Data Association Filter in the absence of truth data

Content Provider	IEEE Xplore Digital Library
Author	Powers, R.M. Pao, L.Y.
Copyright Year	2004
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA (Powers, R.M.; Pao, L.Y.)
Abstract	Of significant interest in the practical application of data association algorithms to target tracking in cluttered environments is how to determine track-loss in the absence of truth data. An approach is laid out for the Probabilistic Data Association Filter (Bar-Shalom and Fortmann, 1988) where the predicted measurement innovations covariance is used to define nominal "tracking" and "track-lost" regimes, and the sample variance of the "effective" filter innovations (prediction errors) is the metric used to determine the regime in a two-class decision rule. A major advantage of this method is that confidence intervals can be placed on the probabilities of both correctly and incorrectly identifying the regimes. Theoretical approximations of the conditional mean and distribution of the sample innovations variance in the tracking and track-lost regimes are proposed for use in construction of the decision rule. Simulation results demonstrating the method are provided.
Starting Page	4316
Ending Page	4323
File Size	204490
Page Count	8
File Format	PDF
ISBN	0780386825
ISSN	01912216
DOI	10.1109/CDC.2004.1429430
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-12-14
Publisher Place	Bahamas
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filters Technological innovation Target tracking Acoustic measurements Electromagnetic measurements State estimation Clutter Gain measurement Testing Acoustic sensors
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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