Global cost of assignment in the TBM framework for association of uncertain ID reports

Autor:	Branko Ristic, Philippe Smets
Rok vydání:	2007
Předmět:	Mathematical optimization Volume of interest Monte Carlo method Complex system Aerospace Engineering False alarm Transferable belief model Belief function theory Algorithm Statistical power Mathematics Constant false alarm rate
Zdroj:	Aerospace Science and Technology. 11:303-309
ISSN:	1270-9638
DOI:	10.1016/j.ast.2006.10.008
Popis:	Suppose we are given multiple independent reports on the count and identification (class, type, allegiance) of objects that are present in a certain volume of interest. The reports are uncertain (random and non-specific) and collected with the probability of detection P d 1 and the probability of false alarm P f > 0 . The problem is to estimate the actual number of objects and their true identity. Adopting the formalism of the belief function theory as interpreted by the transferable belief model (TBM), a solution is proposed which maximises the plausibility of the global assignment cost of identification reports. The proposed global cost of assignment is shown by Monte Carlo simulations to outperform its ad hoc alternatives.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::142973af51cb41f59f8b6e157a23638d https://doi.org/10.1016/j.ast.2006.10.008 Zobrazit plný text záznamu Full Text from ScienceDirect