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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.
Zajic et al. (Tue,) studied this question.