Information for fusion management and performance estimation

Ronald P. S. Mahler

doi:10.1117/12.327137

17 July 1998 Information for fusion management and performance estimation

Ronald P. S. Mahler

Proceedings Volume 3374, Signal Processing, Sensor Fusion, and Target Recognition VII; (1998) https://doi.org/10.1117/12.327137
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

This paper describes a unified, theoretically rigorous approach for measuring the performance of data fusion algorithms, using information theory. The proposed approach is based on 'finite-set statistics' (FISST), a direct generalization of conventional statistics to multisource, multitarget problems. FISST makes it possible to directly extend Shannon-type information metrics to multisource, multitarget problems. This can be done, moreover, in such a way that mathematical 'information' can be defined and measured even though an evaluator/end-user may have conflicting or even subjective definitions of what 'informative' means. The result is a scientifically defensible means of (1) comparing the performance of two algorithms with respect to a 'level playing field' when ground truth is known; (2) estimating the internal on-the-fly effectiveness of a given algorithm when ground truth is not known; and (3) dynamically choosing between algorithms (or different modes of a multi-mode algorithm) on the basis of the information content they provide.

Citation Download Citation

Ronald P. S. Mahler "Information for fusion management and performance estimation", Proc. SPIE 3374, Signal Processing, Sensor Fusion, and Target Recognition VII, (17 July 1998); https://doi.org/10.1117/12.327137

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