An adaptive fusion model for distributed detection systems with unequiprobable sources

Author

Yuzheng Zhang, New Jersey Institute of Technology

Document Type

Thesis

Date of Award

Fall 1-31-1994

Degree Name

Master of Science in Electrical Engineering - (M.S.)

Department

Electrical and Computer Engineering

First Advisor

Nirwan Ansari

Second Advisor

Joseph Frank

Third Advisor

Edwin Hou

Abstract

In a traditional communication system, a single sensor such as a radar or a sonar is used to detect targets. Since the reliability of a single sensor is limited, distributed detection systems in which several sensors are employed simultaneously have received increasing attention in recent years. We consider a distributed detection system which consists of a number of independent local detectors and a fusion center. Chair and Varshney have derived an optimal decision rule for fusing decisions based on. the Baysian criterion. To implement such a rule, the probability of detection P_D and the probability of false alarm P_F for each local detector must be known. This thesis introduces an adaptive fusion model using the fusion result as a supervisor to estimate the P_D and P_F The fusion results are classified as "reliable" and "unreliable". Reliable results will be used as a reference to update the weights in the fusion center. Unreliable results will be discarded. The thesis concludes with simulation results which conform to the analysis.

Recommended Citation

Zhang, Yuzheng, "An adaptive fusion model for distributed detection systems with unequiprobable sources" (1994). Theses. 1231.
https://digitalcommons.njit.edu/theses/1231