A New Decentralized Data Fusion Algorithm with Feedback Framework Based on the Covariance Intersection Method
The main objective of this paper is to analyze models, techniques, algorithms and infrastructures needed to complete decentralized data fusion. It is often to use the Simple Tracking Fusion Algorithm in decentralized data fusion for Multi-sensor. But that algorithm is on the hypothesis that the output of each local filter is uncorrelated. If the fusion result is given back to each local filter, the output of the local filter will has correlation with each other. For that case, if still using the Simple Tracking Fusion Algorithm, the fusion data will lose consistency. But in the Covariance Intersection Algorithm, it is unnecessary to consider the correlation of each local filter. In this paper, a new decentralized data fusion algorithm with feedback framework based on the Covariance Intersection algorithm is proposed for Multi-sensor. The simulation results show the effectiveness and robustness of the proposed algorithm.
decentralized computer feedback framework covariance intersection (CD data fusion
Kun Feng Xue-Guang Zhou Qi Zhang Li Duan
College of Electronic Engineering Naval University of Engineering Hubei Wuhan, 430033, China
国际会议
太原
英文
338-341
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）