Blind adaptive decision fusion for distributed detection

Ghasem Mirjalily, Zhi Quan Luo, Timothy N. Davidson, Élo Bossé

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

We consider the problem of decision fusion in a distributed detection system. In this system, each detector makes a binary decision based on its own observation, and then communicates its binary decision to a fusion center. The objective of the fusion center is to optimally fuse the local decisions in order to minimize the final error probability. To implement such an optimal fusion center, the performance parameters of each detector (i.e., its probabilities of false alarm and missed detection) as well as the a priori probabilities of the hypotheses must be known. However, in practical applications these statistics may be unknown or may vary with time. We develop a recursive algorithm that approximates these unknown values on-line. We the use these approximations to adapt the fusion center. Our algorithm is based on an explicit analytic relation between the unknown probabilities and the joint probabilities of the local decisions. Under the assumption that the local observations are conditionally independent, the estimates given by our algorithm are shown to be asymptotically unbiased and converge to their true values at the rate of O(1/k1/2) in the rms error sense, where k is the number of iterations. Simulation results indicate that our algorithm is substantially more reliable than two existing (asymptotically biased) algorithms, and performs at least as well as those algorithms when they work.

Original languageEnglish (US)
Pages (from-to)34-52
Number of pages19
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume39
Issue number1
DOIs
StatePublished - Jan 2003

Bibliographical note

Funding Information:
This research is supported by a research grant from the Natural Sciences and Engineering Research Council of Canada and by a grant from the Defense Research Establishment Valcartier (DREV), Québec, Canada. The second author is also supported by the Canada Research Chair programme.

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