Multi-Sensor Multi-Target Detection Based on Joint Probability Density

  • Can Xu
  • Zhi Li
  • Lei Shi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 215)


Joint probability density algorithm (JPDA) is extended to multi-sensor multi-target detection based on ‘Clean’ method. Key content and characteristic of JPDA in false intersection points eliminating are introduced. An iterative method for multi-sensor multi-target detection is put forward. Based on target that has been detected by peak searching, an inverse probability density function is proposed which is able to eliminate both the detected target and false intersection points. A new joint probability density matrix is constructed and all the targets can be detected through iterative process. The feasibility and validity are verified through simulation.


Multi-sensor multi-target detection Inverse joint probability density Clean method 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.The Academy of EquipmentBeijingChina

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