Paper
27 July 1999 Practical information-based data fusion performance evaluation
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Abstract
The ability to meaningfully assess the competence of algorithms is a crucial part of developing and comparing practical systems. Moreover, the importance of metrology has increased because of the emergence of fusion strategies such as adaptive fusion and fusion management, which require that Measures of Performance, Effectiveness, and Robustness be examined with greater seriousness. It would seem, therefore, that few things could be as important as achieving a scientific understanding of measurement. In reality, probably no other vital aspect of multisource-multisensor data fusion has been less glamorous, more heuristic, more poorly understood, and less a subject of deep examination than has been metrology. In this paper we present preliminary findings of an ongoing project on scientific performance evaluation for multisource-multisensor data fusion, sponsored by Air Force Research Laboratories, Rome NY.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tim Zajic and Ronald P. S. Mahler "Practical information-based data fusion performance evaluation", Proc. SPIE 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII, (27 July 1999); https://doi.org/10.1117/12.357148
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Cited by 12 scholarly publications.
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KEYWORDS
Data fusion

Detection and tracking algorithms

Sensors

Algorithm development

Metrology

Monte Carlo methods

Molybdenum

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