Data association performance model

Michael A. Kovacich

doi:10.1117/12.283964

29 October 1997 Data association performance model

Michael A. Kovacich

Proceedings Volume 3163, Signal and Data Processing of Small Targets 1997; (1997) https://doi.org/10.1117/12.283964
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

This paper extends the two set data association performance model developed by Mori, et al to include miss detections and bias. The referenced paper developed an analytical model for the probability of correct association of two data sets, called 'tracks' and 'measurements,' using an optimal 2 dimensional assignment algorithm, where the 'true' objects are distributed uniformly but at random in a circular disk. For these true objects, measurements are obtained by adding independent random errors with the same covariance. Tracks are obtained in the same way except a different, fixed covariance is used. Finally, one of the data sets includes an additional distribution of random points, considered 'false alarms.' This paper extends their results to obtain an analytical model that accounts for bias between the data sets and missed detections in either data set. The analytical model is useful in assessing the impact of system requirements for sensor sensitivity, random error and inter-sensor bias error on measurement-to- measurement, measurement-to-track or track-to-track association.

Citation Download Citation

Michael A. Kovacich "Data association performance model", Proc. SPIE 3163, Signal and Data Processing of Small Targets 1997, (29 October 1997); https://doi.org/10.1117/12.283964

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