Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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Similarity Analysis Between SAR Target Images Based on Siamese Network

Siamese 네트워크 기반 SAR 표적영상 간 유사도 분석

  • Park, Ji-Hoon (Defense AI Technology Center, Agency for Defense Development)
  • 박지훈 (국방과학연구소 국방인공지능기술센터)
  • Received : 2021.09.29
  • Accepted : 2022.08.20
  • Published : 2022.10.05
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Abstract

Different from the field of electro-optical(EO) image analysis, there has been less interest in similarity metrics between synthetic aperture radar(SAR) target images. A reliable and objective similarity analysis for SAR target images is expected to enable the verification of the SAR measurement process or provide the guidelines of target CAD modeling that can be used for simulating realistic SAR target images. For this purpose, this paper presents a similarity analysis method based on the siamese network that quantifies the subjective assessment through the distance learning of similar and dissimilar SAR target image pairs. The proposed method is applied to MSTAR SAR target images of slightly different depression angles and the resultant metrics are compared and analyzed with qualitative evaluation. Since the image similarity is somewhat related to recognition performance, the capacity of the proposed method for target recognition is further checked experimentally with the confusion matrix.

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References

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