Distributed Clustering Method for Cooperative Sensing
LI Chen1, LIANG Xiaoxi1, LIANG Junli2, LIU Ruikai2, YE Zhonghua2,3
1. Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109,China;
2. School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China;
3. School of Automation and Engineering, Xian University of Technology, Xi‘an 710048, Shaanxi, China
Abstract:This paper presents a new distributed clustering method for cooperative sensing to solve the problem of multi-target information processing under the condition of decentralized cooperative sensing. Firstly, it formulates a new mathematical model for consensus class center computation with locally averaged data. Secondly, it enables all the sensing equipment to compute in parallel and exchange only the information with its neighboring nodes to protect the privacy of the captured data. Finally, all the equipment obtain the consensus class center and the clustering results when the network is stable. The experiment results prove that the distributed clustering method can make full use of the store, computation, and communication ability of the equipment to complete the clustering task without exchanging massive data.