首页    期刊浏览 2024年11月29日 星期五
登录注册

文章基本信息

  • 标题:Distributed State Estimation of Moving Targets Using Cyclic Simultaneous Perturbation Stochastic Approximation ⁎
  • 本地全文:下载
  • 作者:Victoria Erofeeva ; Oleg Granichin
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:23
  • 页码:218-223
  • DOI:10.1016/j.ifacol.2018.12.038
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractSensor networks comprised of multiple nodes with sensing, processing and communication capabilities are ubiquitous in tracking systems. However, when a tracking system is required to track a large number of targets, the computation and communication loads arise. One possible solution is to use a distributed scheme. In this paper we propose a distributed multiple target tracking algorithm, which takes into account restrictions on the sensor network functioning. Our method is based on the modification of Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm with a perturbation on the input. For the proposed algorithm we get an upper bound of residual between estimates and show the simulation results.
  • 关键词:Keywordssensor networkdistributed estimationstochastic approximationtarget trackingcommunication constraintscomputational constraints
国家哲学社会科学文献中心版权所有