Adaptive fusion model for distributed detection system

Bin-Ou Zhu; Nirwan Ansari; Edwin Sui Hoi Hou

doi:10.1117/12.131663

1 November 1992 Adaptive fusion model for distributed detection system

Bin-Ou Zhu, Nirwan Ansari, Edwin Sui Hoi Hou

Proceedings Volume 1828, Sensor Fusion V; (1992) https://doi.org/10.1117/12.131663
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

Abstract

There has been a growing interest in developing efficient and reliable distributed detection systems for target recognition and communications. Chair and Varshney have derived an optimal decision rule for fusing decisions based on the Bayesian criterion. To implement the rule, the probability of detection P_D and the probability of false alarm P_F for each detector must be known, but this information is not always available in practice. This paper presents an adaptive fusion model which estimate the P_D and P_F adaptively during the decision fusing process. The estimation is implemented by a simple statistical method. That is, the estimates for P_D and P_F of the ith detector are obtained by counting the number of its decisions that are considered to be correct and incorrect, respectively. Since reference signals are not given, whether the decision of a local detector is considered correct or incorrect is arbitrated by the fused decision of all the other local detectors; that is, the fused decision of all other local detectors is used as the reference for the ith detector. Furthermore, in the work, the fused results of the other local decisions are classified as 'reliable' and 'unreliable'. Only reliable decisions are used to develop the decision rule. Analysis on classifying the fused decisions in terms of reducing estimation error is given, and simulation results which conform to our analysis are presented.

Citation Download Citation

Bin-Ou Zhu, Nirwan Ansari, and Edwin Sui Hoi Hou "Adaptive fusion model for distributed detection system", Proc. SPIE 1828, Sensor Fusion V, (1 November 1992); https://doi.org/10.1117/12.131663

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available