Abstract
The measurement accuracy of radar cross section (RCS) based on radar image is usually affected by the image quality. The sidelobe and clutter in the image will reduce the accuracy of RCS measurement. In order to solve the problem, a RCS measurement method based on near-field L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> regularized three-dimensional (3D) synthetic aperture radar (SAR) imaging is proposed. Compared with the traditional matched filtering (MF) method, L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> -regularization method can effectively improve the quality of 3D SAR image, such as clutter and sidelobe suppression. Firstly, the near-field echo is processed by MF to obtain the three-dimensional image of the scene. Then, an L <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> -regularization technique based on 3D SAR image is used to suppress the sidelobe and clutter. Next, the far-field compensation factor is used to obtain the far-field RCS of the target. Finally, the simulation results show that the proposed method can effectively improve the image quality and RCS measurement accuracy.
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