Sub-Aperture Synthetic Aperture Radar Imaging of Fixed-Platform Beam-Steering Radar for Blast Furnace Burden Surface Detection

Abstract

Due to the scheme of fixed-platform beam-steering radar and the space of the blast furnace being subjected to harsh environmental influences, the traditional detection methods of burden surface are limited by geometric distortion, noncoherent clutter, and noise interference, which leads to an increase in the image entropy value and the equivalent number of views, makes the density distribution of burden surface show a diffuse state, and greatly affects the stability and accuracy. In this paper, a new fixed-platform beam-steering radar synthetic aperture radar imaging method (FPBS-SAR) is proposed in the sensory domain of the blast furnace environment. From the perspective of fixed-platform beam-steering radar motion characteristics, the target range–azimuth coupled distance history model under the sub-aperture is established, the azimuthal Doppler variation characteristics of the fixed-platform beam-steering process are analyzed, and the compensation function of the transform domain for geometric disturbance correction is proposed. For noncoherent noise suppression in blast furnaces, the trimmed geometric mean-order-likelihood CFAR method is proposed to take into account the information of burden surface and clutter suppression. To verify the method, point target simulation and imaging for the industrial field measurement data are carried out. The results indicate that geometric distortion is well eliminated, the image entropy value and the equivalent number of views have decreased, and noncoherent noise in blast furnaces is suppressed.

Keywords

• blast furnace (BF)
• beam steering radar
• burden surface imaging
• non-linear spatial correction
• trimmed geometric mean order likelihood CFAR (TGMOL-CFAR)