ISBN: 978-981-18-3959-7 DOI: 10.18178/wcse.2022.06.036
Multi-target Localization Technology Fused with Clustering Algorithm
Abstract— At present, wireless sensor networks are widely used in passive target localization. Aiming at the problem of low positioning accuracy in the compressed sensing localization algorithm based on Bayesian learning, a multi-target localization technology fused with clustering algorithm is proposed. Firstly, the multitarget problem is transformed into sparse signal reconstruction problem by Using Bayesian learning algorithm. Then, based on the target location obtained by multiple sparse recovery, clustering operation is performed to achieve accurate location. Simulation results show that the proposed method improves positioning accuracy and has strong robustness.
Index Terms—Wireless sensor network, Bayesian learning, Compression perception, Clustering algorithm, Sparse signal reconstruction
Chen Cheng, Li Ning, Guo Yan, Sheng Jinfeng, Li Huajing
School of Communication Engineering, Army Engineering University of PLA, CHINA
Cite:Chen Cheng, Li Ning, Guo Yan, Sheng Jinfeng, Li Huajing, "Multi-target Localization Technology Fused with Clustering Algorithm, " Proceedings of 2022 the 12th International Workshop on Computer Science and Engineering (WCSE 2022), pp. 253-261, June 24-27, 2022.