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.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
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
Copy
@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},}
Copy
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 -