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Signal Sorting Based on SVC & K-Means Clustering in ESM Systems

  • Qiang Guo
  • Wanhai Chen
  • Xingzhou Zhang
  • Zheng Li
  • Di Guan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4233)

Abstract

As radar signal environments become denser and radar signals become more complex, the task of an ESM operator becomes more difficult. This paper presented a de-interleaving/recognition system of radar pulses based on the combination of SVC and K-means clustering. Compared the conventional de-interleaving system, it can produce more complex and compact clustering boundaries according to the distribution characteristics of data set and has good generalization performance. The simulation experiment result shows that the system can sort efficiently radar signals in the high density and complex pulses environment.

Keywords

Support Vector Machine Radar Signal Radar Pulse High Dimensional Feature Space Cluster Boundary 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Qiang Guo
    • 1
  • Wanhai Chen
    • 1
  • Xingzhou Zhang
    • 1
  • Zheng Li
    • 2
  • Di Guan
    • 3
  1. 1.College of Information and Communication EngineeringHarbin Engineering UniversityHarbinChina
  2. 2.Southwest Research Institute of Electronic EquipmentChengduChina
  3. 3.Harbin Normal UniversityHarbinChina

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