RCS Prediction Method from One-Dimensional Intensity Data in Near-Field
スポンサーリンク
概要
- 論文の詳細を見る
Radar Cross Section (RCS) can be obtained from near-field data by using near-field to far-field RCS transformation methods. Phase errors in near-field data cause the degradation of the prediction accuracy. In order to overcome the difficulty, we propose the far-field RCS prediction method from one-dimensional intensity data in near-field. The proposed method is derived by extending the phase retrieval method based on the Gerchberg-Saxton algorithm with the use of the relational expression between near-fields and scattering coefficients. The far-field RCS can be predicted from the intensity data of scattered fields measured at two different ranges. The far-field RCS predicted by the proposed method approximately coincides with the computed one. The proposed method also has significant advantages of simple and efficient algorithm. The proposed method is valuable from a practical point of view.
- (社)電子情報通信学会の論文
- 2008-07-01
著者
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MIYASHITA Hiroaki
Information Technology R&D Center, Mitsubishi Electric Corp.
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KONISHI Yoshihiko
Information Technology R&D Center, Mitsubishi Electric Corp.
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Miyashita Hiroaki
Information Technology R&d Center Mitsubishi Electric Corp.
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Miyashita Hiroaki
Mitsubishi Electric Corporation
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Konishi Yoshihiko
Information Technology R&d Center Mitsubishi Electric Corp.
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Miyashita Hiroaki
Mitsubishi Electric Corp. Kamakura‐shi Jpn
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Konishi Yoshihiko
Mitsubishi Electric Corp. Kamakura‐shi Jpn
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INASAWA Yoshio
Information Technology R&D Center, Mitsubishi Electric Corporation
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Inasawa Yoshio
Information Technology R&d Center Mitsubishi Electric Corporation
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Konishi Yoshihiko
The Information Technology R&d Center Mitsubishi Electric Corporation
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Inasawa Yoshio
Information Technology R&D Center, Mitsubishi Electric Corporation
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