A track purity approach for tracking metrics

Proper analysis of a simulated sensor tracking problem requires the ability to correctly determine the true trajectory that underlies each track. Traditionally, kinematic assignment of tracks to truth has been used. More recently, a "track-purity" approach has been proposed to both assess the performance of kinematic truth-to-track assignment algorithms and to overcome some of the anomalies that occur when kinematic assignment is used; particularly for unresolved closely-spaced targets. The track-purity approach relies on a simulation\´s unique ability to identify which truth objects contribute to each measurement. Less clear are the following issues: 1) When a measurement is formed, what is the percentage contribution from each truth object in each measurement primitive, 2) How should truth contributions be combined and modified as measurement data are passed through the various data and signal processing algorithms found in a typical monopulse phased-array radar (e.g., closely-spaced unresolved objects, direction-of-arrival estimation, measurement clustering, data assignment, filtering, and multi-sensor fusion), 3) How should truth content values be used to produce a content-based association between tracks and truth? The complete process for establishing the truth content of a track from the initial truth content of each detection to the final truth content at the output of track filtering is discussed. This discussion includes the effects of measurement clustering and centroiding, ambiguity in the measurement-to-track assignment, filter gains used to update the track\´s state estimate, and a truth-contribution-based method for establishing track-to-truth assignment.