NDLI: Measurement-to-track cost assignment computation when tracking with the IMM estimator

Content Provider	IEEE Xplore Digital Library
Author	Ehrman, L. Register, A. Blair, W.D.
Copyright Year	2005
Description	Author affiliation: Georgia Tech Res. Inst., Smyrna, GA (Ehrman, L.; Register, A.; Blair, W.D.)
Abstract	In the multi-target tracking problem, the association of measurements to tracks is typically conducted using an m times n cost matrix, where there are m tracks and n measurements. Each element of this cost matrix is computed based on some measure of the statistical distance between the estimated track state and the measurement. A common approach is to calculate a negative log-likelihood value that includes the uncertainty of the estimate and measurement. When tracking with an interacting multiple model (IMM) estimator, multiple mode likelihood values are possible for each measurement/track pair. Computing the cost assignment matrix given these likelihoods is a critical design issue. This paper compares two approaches for computing the cost assignment matrix. The first computes the likelihood with the mode that maximizes the likelihood for each given measurement. An alternate approach evaluates the pure likelihood of the Gaussian mixture. To focus on data association, we assume that the objects are perfectly resolved. The impact of imperfect object resolution is reserved for future work
Starting Page	2043
Ending Page	2052
File Size	337305
Page Count	10
File Format	PDF
ISBN	0780388704
DOI	10.1109/AERO.2005.1559496
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational efficiency Radar tracking Costs Acceleration State estimation Monte Carlo methods Gravity Target tracking Covariance matrix Registers
Content Type	Text
Resource Type	Article

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