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  • 标题:Improved Mult-agent Tracking Algorithm Based on Gaussian Mixture Particle PHD Filter
  • 本地全文:下载
  • 作者:Qing Lin ; Pei Cao ; Dinggan Liao
  • 期刊名称:International Journal of Multimedia and Ubiquitous Engineering
  • 印刷版ISSN:1975-0080
  • 出版年度:2015
  • 卷号:10
  • 期号:2
  • 页码:227-236
  • DOI:10.14257/ijmue.2015.10.2.21
  • 出版社:SERSC
  • 摘要:The paper proposes Gaussian mixture particle probability hypothesis density filter(PHD) algorithm ,which can effectively solve the problem that the object number is changing or unknown, based on particle PHD filter. This algorithm calculates the object number and state by recursive procedure, avoiding the uncertainty of target state estimation caused by particle sampling and clustering. Gaussian mixture particle is introduced to effectively maintain the multi-modal distribution of each target,reducing the complexity of calculation.
  • 关键词:Gaussian Particle Filter; Multi-target Tracking; Probability Hypothesis Density; Mixture Particle Filter
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