Measures for evaluating sea mine identification processing performance and the enhancements provided by fusing multisensor/multiprocess data via an M-out-of-N voting scheme

Manuel F. Fernandez; Tom Aridgides

doi:10.1117/12.487774

11 September 2003 Measures for evaluating sea mine identification processing performance and the enhancements provided by fusing multisensor/multiprocess data via an M-out-of-N voting scheme

Manuel F. Fernandez, Tom Aridgides

Author Affiliations +

Proceedings Volume 5089, Detection and Remediation Technologies for Mines and Minelike Targets VIII; (2003) https://doi.org/10.1117/12.487774
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

This paper indicates how sea=test data collected by N independent sensors - or alternatively, data collected by a single sensor, but processed through N independent processing strings - can be used to model, estimate, and predict the performance of a mine identification system. The proposed procedure exploits the information supplied by the sensors/processes (namely, the locations of their individual detection reports), to approximate the probabilities of detection and false alarm in terms of the ratios of the numbers of reports, as seen by the various combinations of sensors. A constrained Least-Squares procedure, fitting the products of these ratios as dictated by their independence equivalencies, is then used to estimate the individual sensor/process probabilities of detection, of false alarm caused by mine-like objects, and of false alarm due to noise. We can then obtain the corresponding probabilities that can be expected after fusing the data with an M-out-of-N voting process.

Citation Download Citation

Manuel F. Fernandez and Tom Aridgides "Measures for evaluating sea mine identification processing performance and the enhancements provided by fusing multisensor/multiprocess data via an M-out-of-N voting scheme", Proc. SPIE 5089, Detection and Remediation Technologies for Mines and Minelike Targets VIII, (11 September 2003); https://doi.org/10.1117/12.487774

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