Paper
26 May 1995 Performance evaluation of single-target tracking in clutter
Oliver E. Drummond
Author Affiliations +
Abstract
Performance evaluation is fairly straight forward when tracking a single bright target. Tracking a dim target in clutter, on the other hand, can present some challenges in performance evaluation. For example, a target track can be a false track. A false track is one based primarily on clutter points or false signals rather than the target. How is a false track to be identified and what measures of performance should be used to account for a false track? In comparing two different trackers or two variants of the same tracker, how can the performance be evaluated effectively and fairly? One tracker might acquire the target earlier (at greater range) than the other, yet not track as accurately. In some scenarios one tracker might even miss the target completely, that is, exhibit a missed track. This is another performance evaluation issue that must be addressed. This paper presents a two-step method for evaluating performance of tracking a single target in clutter. The first step classifies the target track as valid, missed or false. Various tracking measures of performance are then computed in the second step. This two-step approach provides a systematic method for tracker performance evaluation. More importantly, this methodology is designed to permit a fair evaluation and comparison oftwo or more competing trackers. KEYWORDS: Performance Evaluation, Measures Of Performance, Trackers, Tracking, Single Target Tracking, Multiple Object Tracking, Multiple Track Processing, Multiple Sensor Tracking, False Tracks.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Oliver E. Drummond "Performance evaluation of single-target tracking in clutter", Proc. SPIE 2468, Acquisition, Tracking, and Pointing IX, (26 May 1995); https://doi.org/10.1117/12.210449
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Cited by 4 scholarly publications.
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KEYWORDS
Monte Carlo methods

Signal processing

Detection and tracking algorithms

Target acquisition

Distance measurement

Error analysis

Sensors

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