Adaptive decision fusion for unequiprobable sources

Author

Ansari, N. ; Chen, J.-G. ; Zhang, Y.-Z.

Author_Institution

Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA

Volume

144

Issue

3

fYear

1997

fDate

6/1/1997 12:00:00 AM

Firstpage

105

Lastpage

111

Abstract

An optimal decision rule has been derived by Chair and Varshney (1986) for fusing decisions based on the Bayesian criterion. However, to implement such a rule, the miss probability P_M and the probability of false alarm P_F for each local detector must be known, and these are not readily available in practice. To circumvent this situation, an adaptive fusion system for equiprobable sources has been developed. The system is extended to unequiprobable sources; thus its practicality is enhanced. An adaptive fusion model using the fusion result as a supervisor to estimate the P_M and P_F is introduced. The fusion results are classified as `reliable´ and `unreliable´. Reliable results are used as a reference to update the weights in the fusion centre. Unreliable results are discarded. The convergence and error analysis of the system are demonstrated theoretically and by simulations. The paper concludes with simulation results that conform to the analysis

Keywords

Bayes methods; adaptive signal detection; convergence of numerical methods; decision theory; error analysis; probability; sensor fusion; Bayesian criterion; adaptive decision fusion; adaptive fusion model; adaptive fusion system; convergence; distributed detection systems; equiprobable sources; error analysis; fusion centre; fusion results; local detector; miss probability; optimal decision rule; probability of false alarm; reliable results; simulation results; supervisor; unequiprobable sources; unreliable results;

fLanguage

English

Journal_Title

Radar, Sonar and Navigation, IEE Proceedings -

Publisher

iet

ISSN

1350-2395

Type

jour

DOI

10.1049/ip-rsn:19971176

Filename

600892