Object Georeferencing in UAV-Based SAR Terrain Images

Abstract

Synthetic aperture radars (SAR) allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV). The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

A classification technique of civil objects by artificial neural networks using estimation of entropy on synthetic aperture radar images

“…The methods using automatic detection and recognition of the objects over the underlying surface are required in the tasks of terrain mapping, aerial photography, and video fixation (Pillai et al, 2008;Soumekh, 1999). The physical principles of radar recognition are based on the received echo signals from radar contrast targets, Doppler shifts of moving objects, and changes in the polarization structure of the reflected wave (Lee and Pottier, 2009). One of the prospective directions is the use of unmanned aerial vehicles (UAVs), which monitor the Earth's surface by synthetic aperture radar (SAR).…”

“…One of the prospective directions is the use of unmanned aerial vehicles (UAVs), which monitor the Earth's surface by synthetic aperture radar (SAR). These radar systems ensure images in real time are received at different altitudes and varying aspect angles (Moreira et al, 2013;Long et al, 2019).…”

“…The modern development of SAR includes the use of the so-called homogeneous environment and applications for MIMO systems (Moreira et al, 2013). An important characteristic of the automatic target recognition (ATR) is a con-stant false-alarm rate (CFAR) (Zhoufeng et al, 2002;Jung et al, 2009), the type of radar polarization (Lee and Pottier, 2009), and SAR imaging modes (stripmap or spotlight mode). The potential accuracy can reach 0.3 m with a linear resolution using multilook processing in the spaceborne radar (Kim et al, 2014;Novak et al, 1998) (Fig.…”