Abstract
Autofocus has attracted wide attention for unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) systems, because autofocus process is crucial and difficult when the phase error is spatially dependent on both range and azimuth directions. In this paper, a novel two-dimensional spatial-variant map-drift algorithm (2D-SVMDA) is developed to provide robust autofocusing performance for UAV SAR imagery. This proposed algorithm combines two enhanced map-drift kernels. On the one hand, based on the azimuth-dependent phase correction, a novel azimuth-variant map-drift algorithm (AVMDA) is established to model the residual phase error as a linear function in the azimuth direction. Then the model coefficients are efficiently estimated by a quadratic Newton optimization with modified maximum cross-correlation. On the other hand, by concatenating the existing range-dependent map-drift algorithm (RDMDA) and the proposed AVMDA in this paper, a phase autofocus procedure of 2D-SVMDA is finally established. The proposed 2D-SVMDA can handle spatial-variance problems induced by strong phase errors. Simulated and real measured data are employed to demonstrate that the proposed algorithm compensates both the range- and azimuth-variant phase errors effectively.
Highlights
The synthetic aperture radar (SAR) system performs well in both military and civilian fields such as military reconnaissance, geographical mapping, and disaster warning for its all-weather and all-time working capability of two-dimensional high-resolution imaging [1,2,3,4,5]
For unmanned aerial vehicle (UAV) SAR systems [10,11,12] working at a low altitude, their flight trajectory is usually disturbed by severe atmospheric turbulence because of the small size and light weight of UAV platform [13], which inevitably causes serious blurring and geometric distortion in SAR images
Aimed at solving the spatial-variant phase error problem, first we develop a novel azimuth-variant map-drift algorithm (AVMDA) for autofocusing UAV SAR imagery
Summary
The synthetic aperture radar (SAR) system performs well in both military and civilian fields such as military reconnaissance, geographical mapping, and disaster warning for its all-weather and all-time working capability of two-dimensional high-resolution imaging [1,2,3,4,5]. It has high azimuth resolutions due to relative movement between antenna and target. This platform movement poses difficulties for accurate imaging [6], and motion compensation (MOCO) [7,8,9] is an essential procedure for SAR imaging. A high-precision inertial navigation system (INS) which consists of inertial measurement unit (IMU) and global position system (GPS) is necessarily mounted on the UAV platform to record the real-time velocity and position information. Most UAV SAR platforms are only equipped with a medium- or low-accuracy
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