13 September 2007 Metrics for evaluating track covariance consistency
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Abstract
The primary components of a target track are the estimated state vector and its error variance-covariance matrix (or simply the covariance). The estimated state indicates the location and motion of the target. The track covariance should indicate the uncertainty or inaccuracy of the state estimate. The covariance is computed by the track processor and may or may not realistically indicate the inaccuracy of the state estimate. Covariance Consistency is the property that a computed variance-covariance matrix realistically represents the covariance of the actual errors of the estimate. The computed covariance of the state estimation error is used in the computations of the data association processing function; consequently, degraded track consistency might cause misassociations (correlation errors) that can substantially degrade track performance. The computed covariance of the state estimation error is also used by downstream functions, such as the network-level resource management functions, to indicate the accuracy of the target state estimate. Hence, degraded track consistency can mislead those functions and the war fighter about how accurate each target track is. In the past, far more attention has been given to improving the accuracy of the estimated target state than in improving the track covariance consistency. This paper addresses performance metrics of covariance consistency. Monte Carlo simulation results illustrate the characteristics of the proposed metrics of covariance consistency.
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Oliver E. Drummond, Oliver E. Drummond, Terrence L. Ogle, Terrence L. Ogle, Steven Waugh, Steven Waugh, } "Metrics for evaluating track covariance consistency", Proc. SPIE 6699, Signal and Data Processing of Small Targets 2007, 669916 (13 September 2007); doi: 10.1117/12.740303; https://doi.org/10.1117/12.740303
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