Research Output
A novel SAR target detection algorithm based on contextual knowledge
  This paper proposes a Synthetic Aperture Radar (SAR) vehicle target detection algorithm based on contextual knowledge. The proposed algorithm firstly obtains the general classification of SAR image with a Markov Random Field (MRF)-based segmentation algorithm; then modifies the prior target presence probability utilizing terrain types, distances to boundary and target aggregation degree; finally gains the detection results using improved Cell Averaging-Constant False Alarm Rate (CA-CFAR). Detections with real SAR image data show that this algorithm can effectively improve target detection rate and reduce false alarms compared with conventional CA-CFAR.

  • Type:

    Article

  • Date:

    31 December 2013

  • Publication Status:

    Published

  • DOI:

    10.2528/PIER13062403

  • ISSN:

    1070-4698

  • Funders:

    Historic Funder (pre-Worktribe)

Citation

Gao, F., Ru, A., Sun, J., & Hussain, A. (2013). A novel SAR target detection algorithm based on contextual knowledge. Progress In Electromagnetics Research, 142, 123-140. https://doi.org/10.2528/PIER13062403

Authors

Keywords

Synthetic Aperture Radar (SAR); vehicle target detection algorithm; Markov Random Field (MRF)-based segmentation algorithm; detection rates

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