A Geometric Auto-Calibration Method for Multiview UAV-Borne FMCW SAR Images

In recent years, the geometric calibration for synthetic aperture radar (SAR) has been developing toward automation and lack of ground control points (GCPs). In this case, the calibration equations become ill-conditioned, making the results unstable. The slant range error of unmanned aerial vehicle (UAV)-borne SAR, whose transmitting signal is a frequency modulation continuous wave, is usually spatially variable, which makes this problem more complicated. In this letter, a geometric auto-calibration method for UAV-borne SAR is proposed. First, a robust auto-calibration model is proposed to calibrate the space-varying slant range error. Second, a weighting strategy based on the quality of tie points (TPs) is proposed to further improve the calibration accuracy of this method. Finally, an iterative method based on correcting characteristic values is utilized to find the least squares solution robustly. Simulation results confirm about 70% performance enhancement of the proposed method over the traditional approach. In real-data experiments, the auto-calibration yielded a positioning accuracy improvement to 11.5 cm.