RCS Prediction Method from One-Dimensional Intensity Data in Near-Field

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.