Paper
1 October 1990 Simulation-based test bed for data association algorithms
Donald E. Brown, C. Louis Pittard, Andrew R. Spillane
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Abstract
The problem of associating data in a domain with noisy sensor inputs is of considerable importance in a wide variety of problem areas. Data association algorithms provide an approach for automatically correlating and combining incoming sensor data. A number of association algorithms have been developed; however, evaluating the effectiveness of these algorithms is difficult because traditional evaluation methods fail to provide meaningful meansures of relative merit. These traditional measures are troublesome because the type I and type II errors upon which they are based lose all meaning after reports are combined in a data base. This paper describes a test bed which uses an alternative approach for measuring the performance of association algorithms. Like the traditional measures, the approach described here requires the use of simulated sensor data. The evaluation procedure is based on a measure of the distance between a baseline representation and the representation produced by the association algorithm at some time instant. Two choices for this baseline representation are listed and scores are defmed between these baselines and an algorithm's representation. A description of the test bed architecture which implements this evaluation procedure is provided, as well as, sample outputs from performing algorithm evaluations in the test bed.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Donald E. Brown, C. Louis Pittard, and Andrew R. Spillane "Simulation-based test bed for data association algorithms", Proc. SPIE 1306, Sensor Fusion III, (1 October 1990); https://doi.org/10.1117/12.21630
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KEYWORDS
Sensors

Aluminum

Algorithm development

Distance measurement

Sensor fusion

Environmental sensing

Detection and tracking algorithms

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