• Title/Summary/Keyword: ISAR Autofocusing Technique

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ISAR Imaging of a Real Aircraft Using KOMSAR (KOMSAR를 이용한 실제 항공기 ISAR 영상 제작)

  • Kim, Kyung-Tae;Jeong, Ho-Ryung
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.18 no.7
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    • pp.717-722
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    • 2007
  • Inverse synthetic aperture radar(ISAR) images represent two-dimensional(2-D) spatial distribution of electromagnetic scattering phenomenology against a target. Hence, they are usually used in the areas of automatic target recognition (ATR) or non-cooperative target recognition(NCTR), identifying a target using radar in a long distance. This paper makes use of Korea Miniature Synthetic Aperture Radar(KOMSAR) to generate ISAR images of a real and maneuvering aircraft. The data obtained from KOMSAR are processed to eliminate phase errors due to motion of a target, with the use of entropy-based ISAR autofocusing technique. Results show that we can successfully obtain ISAR images of a real aircraft, and the success of experiments implies that a significant step toward ATR using radar has been established.

Application of Subarray Averaging and Entropy Minimization Algorithm to Stepped-Frequency ISAR Autofocus (부배열 평균과 엔트로피 최소화 기법을 이용한 stepped-frequency ISAR 자동초점 기법 성능 향상 연구)

  • Jeong, Ho-Ryung;Kim, Kyung-Tae;Lee, Dong-Han;Seo, Du-Chun;Song, Jeong-Heon;Choi, Myung-Jin;Lim, Hyo-Suk
    • Proceedings of the KSRS Conference
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    • 2008.03a
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    • pp.158-163
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    • 2008
  • In inverse synthetic aperture radar (ISAR) imaging, An ISAR autofocusing algorithm is essential to obtain well-focused ISAR images. Traditional methods have relied on the approximation that the phase error due to target motion is a function of the cross-range dimension only. However, in the stepped-frequency radar system, it tends to become a two-dimensional function of both down-range and cross-range, especially when target's movement is very fast and the pulse repetition frequency (PRF) is low. In order to remove the phase error along down-range, this paper proposes a method called SAEM (subarray averaging and entropy minimization) [1] that uses a subarray averaging concept in conjunction with the entropy cost function in order to find target motion parameters, and a novel 2-D optimization technique with the inherent properties of the proposed entropy-based cost function. A well-focused ISAR image can be obtained from the combination of the proposed method and a traditional autofocus algorithm that removes the phase error along the cross-range dimension. The effectiveness of this method is illustrated and analyzed with simulated targets comprised of point scatters.

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