Near-distance raw and reconstructed ground based SAR data

Abstract

Presented data includes two datasets named RealSAR-RAW and RealSAR-IMG. The first one contains unprocessed (raw) radar data obtained using Ground Based Synthetic Aperture Radar (GBSAR), while the second one contains images reconstructed using Omega-K algorithm applied to raw data from the first set. The GBSAR system moves the radar sensor along the track to virtually extend (synthesize) the antenna aperture and provides imaging data of the area in front of the system. The used sensor was a Frequency Modulated Continuous Wave (FMCW) radar with a central frequency of 24 GHz and a 700 MHz wide bandwidth which in our case covered the observed scene in 30 steps with 1 cm step size. The measured (recorded) scenes were made on combinations of three test objects (bottles) made of different material (aluminum, glass, and plastic) in different positions. The aim was to develop a small dataset of GBSAR data useful for classification applications focused on distinguishing different materials from sparse radar data.

Keywords

• Synthetic aperture radar
• Ground based SAR
• Raw radar data
• Radar image
• Object classification