Target Assignment Optimization of Heterogeneous Sensor Networks in Urban Environment

Chen Chen, Cheng Zihao, Xu Wei

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Preventing and controlling Low-Slow-Small(LSS) targets are problems to be solved due to their good concealment in urban environment. Consequently, the problem of target assignment is studied in this paper. Firstly, a target assignment model based on heterogeneous sensor networks is proposed. The characteristics of LSS targets and the influence of environmental factors such as climate and terrain are considered on this model. At the same time, the detection capabilities of different detection nodes and collaborative tracking capabilities are also considered. Secondly, an intelligent optimization algorithm GSAPSO based on PSO is proposed to maximize tracking effect of the sensors. Finally, the simulations are used to compare the GSAPSO algorithm with the traditional PSO and GAPSO algorithms. The results demonstrate that the proposed algorithm has better tracking effect.

Original languageEnglish
Title of host publicationProceedings of the 39th Chinese Control Conference, CCC 2020
EditorsJun Fu, Jian Sun
PublisherIEEE Computer Society
Pages1643-1648
Number of pages6
ISBN (Electronic)9789881563903
DOIs
Publication statusPublished - Jul 2020
Event39th Chinese Control Conference, CCC 2020 - Shenyang, China
Duration: 27 Jul 202029 Jul 2020

Publication series

NameChinese Control Conference, CCC
Volume2020-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference39th Chinese Control Conference, CCC 2020
Country/TerritoryChina
CityShenyang
Period27/07/2029/07/20

Keywords

  • Heterogeneous sensor networks
  • PSO
  • Target assignment
  • Urban environment

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Chen, C., Zihao, C., & Wei, X. (2020). Target Assignment Optimization of Heterogeneous Sensor Networks in Urban Environment. In J. Fu, & J. Sun (Eds.), Proceedings of the 39th Chinese Control Conference, CCC 2020 (pp. 1643-1648). Article 9189634 (Chinese Control Conference, CCC; Vol. 2020-July). IEEE Computer Society. https://doi.org/10.23919/CCC50068.2020.9189634