The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
La section efficace radar (RCS) peut être obtenue à partir de données en champ proche en utilisant des méthodes de transformation RCS de champ proche en champ lointain. Les erreurs de phase dans les données en champ proche entraînent une dégradation de la précision de la prédiction. Afin de surmonter cette difficulté, nous proposons la méthode de prédiction RCS en champ lointain à partir de données d'intensité unidimensionnelles en champ proche. La méthode proposée est dérivée de l'extension de la méthode de récupération de phase basée sur l'algorithme de Gerchberg-Saxton avec l'utilisation de l'expression relationnelle entre champs proches et coefficients de diffusion. Le RCS en champ lointain peut être prédit à partir des données d'intensité des champs dispersés mesurées à deux distances différentes. Le RCS en champ lointain prédit par la méthode proposée coïncide approximativement avec celui calculé. La méthode proposée présente également les avantages significatifs d’un algorithme simple et efficace. La méthode proposée est intéressante d’un point de vue pratique.
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Yoshio INASAWA, Hiroaki MIYASHITA, Yoshihiko KONISHI, "RCS Prediction Method from One-Dimensional Intensity Data in Near-Field" in IEICE TRANSACTIONS on Electronics,
vol. E91-C, no. 7, pp. 1167-1170, July 2008, doi: 10.1093/ietele/e91-c.7.1167.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/electronics/10.1093/ietele/e91-c.7.1167/_p
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@ARTICLE{e91-c_7_1167,
author={Yoshio INASAWA, Hiroaki MIYASHITA, Yoshihiko KONISHI, },
journal={IEICE TRANSACTIONS on Electronics},
title={RCS Prediction Method from One-Dimensional Intensity Data in Near-Field},
year={2008},
volume={E91-C},
number={7},
pages={1167-1170},
abstract={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.},
keywords={},
doi={10.1093/ietele/e91-c.7.1167},
ISSN={1745-1353},
month={July},}
Copier
TY - JOUR
TI - RCS Prediction Method from One-Dimensional Intensity Data in Near-Field
T2 - IEICE TRANSACTIONS on Electronics
SP - 1167
EP - 1170
AU - Yoshio INASAWA
AU - Hiroaki MIYASHITA
AU - Yoshihiko KONISHI
PY - 2008
DO - 10.1093/ietele/e91-c.7.1167
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E91-C
IS - 7
JA - IEICE TRANSACTIONS on Electronics
Y1 - July 2008
AB - 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.
ER -