Range-Dependent Map-Drift Algorithm for Focusing UAV SAR Imagery

Abstract

Synthetic aperture radar (SAR) systems mounted on unmanned aerial vehicles (UAVs) are usually sensitive to trajectory deviations that cause serious motion error in the recorded data. In this letter, a novel range-dependent map-drift algorithm (RDMDA) is developed to accommodate the range-variant characteristics of severe motion errors. Utilizing the algorithm as a core estimate, we come up with a robust motion compensation strategy for the UAV SAR imagery. RDMDA outperforms the conventional MDA in both accuracy and robustness while it keeps similar efficiency. Real data experiment shows that the proposed approach is appropriate for precise imaging of UAV SAR systems equipped with only a low-accuracy inertial navigation system.