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Because there may be misassociations, soft-decision association, or extra tracks due to false detections or other causes, performance evaluation of multiple target tracking is more complex than evaluating filter performance. This paper presents a methodology and performance metrics to evaluate tracking in the presence of these and other complications. The goal is to evaluate the various aspects of tracking performance that are of concern to operational users. The emphasis of this paper is performance evaluation of trackers, both single-sensor trackers and distributed trackers that combine data from multiple, distributed sensors. Included are the equations for computing metrics to evaluate completeness, timeliness, track continuity, ambiguity, accuracy, and cross-platform commonality. Cross-platform commonality includes metrics to evaluate how consistent the target tracks are across global trackers at different locations.
Rothrock et al. (Thu,) studied this question.