A Novel Method for Multi-Targets ISAR Imaging Based on Particle Swarm Optimization and Modified CLEAN Technique

Lei Liu, Feng Zhou, Mingliang Tao, Zijing Zhang

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

In multi-targets inverse synthetic aperture radar (ISAR) imaging, range profiles of different target are coupled together, resulting in the failure of traditional mono-target imaging method. A novel multi-targets ISAR imaging method based on particle swarm optimization (PSO) and modified CLEAN technique is proposed in this paper. First, multi-targets are modeled as several separated group-targets in which translational motion of each target is analogous. And then, translational motion of each group-target is modeled as a polynomial, and the polynomial coefficient vector is estimated via the PSO-based iteration. Furthermore, a well-focused image of the group-target can be obtained and extracted via the proposed modified CLEAN technique. Meanwhile, each target can be segmented and extracted based on clustering number estimation and K-means clustering algorithm. Finally, better focused image of each target would be obtained through further traditional mono-target imaging processing. Experimental results verify the validity of the proposed method.

Original languageEnglish
Article number7268838
Pages (from-to)97-108
Number of pages12
JournalIEEE Sensors Journal
Volume16
Issue number1
DOIs
StatePublished - 1 Jan 2016
Externally publishedYes

Keywords

  • clustering algorithm
  • Inverse synthetic aperture radar (ISAR)
  • modified CLEAN
  • multi-targets
  • particle swarm optimization (PSO)

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