A Double Threshold Collaborative Detection Algorithm Based on Mutual Trust Degree Correction

2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering

无线电电子学;计算机科学;材料科学

Lujie, Zhang^1 ; Dechun, G.U.O.^1

School of Information and Electronics, Beijing Institute of Technology, 5 Hainan, Beijing, China^1

关键词: Collaborative detection;    Detection performance;    Detection statistic;    Double threshold;    Mutual trust;    Probability of missed detections;    Single users;    Weight distributions;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/563/5/052024/pdf
DOI  :  10.1088/1757-899X/563/5/052024

来源: IOP

【 摘 要 】

This paper proposes a double threshold detection algorithm based on mutual trust degree correction, in order to reduce the probability of missed detection. First, the algorithm performs mutual trust correction on the local detection statistic of the information fusion center, next, performs information fusion. The algorithm reduces the influence of a single user on the detection result, which is caused by the weight distribution in the information fusion process. The algorithm makes the weight distribution in the information fusion process more reasonable and balanced. The simulation results show that the detection performance of the double threshold detection algorithm modified by the mutual trust matrix is better than that of the traditional double threshold detection algorithm.