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  • 标题:Efficient DoA Tracking of Variable Number of Moving Stochastic EM Sources in Far-Field Using PNN-MLP Model
  • 本地全文:下载
  • 作者:Zoran Stanković ; Nebojša Dončov ; Bratislav Milovanović
  • 期刊名称:International Journal of Antennas and Propagation
  • 印刷版ISSN:1687-5869
  • 电子版ISSN:1687-5877
  • 出版年度:2015
  • 卷号:2015
  • DOI:10.1155/2015/542614
  • 出版社:Hindawi Publishing Corporation
  • 摘要:An efficient neural network-based approach for tracking of variable number of moving electromagnetic (EM) sources in far-field is proposed in the paper. Electromagnetic sources considered here are of stochastic radiation nature, mutually uncorrelated, and at arbitrary angular distance. The neural network model is based on combination of probabilistic neural network (PNN) and the Multilayer Perceptron (MLP) networks and it performs real-time calculations in two stages, determining at first the number of moving sources present in an observed space sector in specific moments in time and then calculating their angular positions in azimuth plane. Once successfully trained, the neural network model is capable of performing an accurate and efficient direction of arrival (DoA) estimation within the training boundaries which is illustrated on the appropriate example.
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