A geometric Cross-Propagation-Calibration method for SAR constellation based on the graph theory

The networking capability of SAR constellations can effectively reduce the average revisit period, which has become a new trend in SAR Earth observation. However, the system electronic delay of several or even dozens of SAR satellites in a constellation must be calibrated and monitored for a long time to ensure high geometric accuracy of the product. In this paper, a geometric cross-propagation-calibration method for SAR constellations is proposed, which can calibrate the slant ranges of the SAR satellites in a constellation without any calibrators. The proposed method constructs a graph from all reference and uncalibrated SAR images involved in a cross-calibration task. For each uncalibrated image, the cumulative calibration error along paths originating from the reference images is estimated, enabling the identification of a path that minimizes this error. Cross-calibration is then performed sequentially along this optimal path. A closed-form expression is derived to estimate the cumulative calibration error along any path, which also reveals the underlying mechanism of error propagation in cross-calibration. Experiments based on real data show that the proposed method enables two China’s microsatellites, Qilu-1 and Xingrui-9, to achieve geometric accuracy of less than 5 m after calibration.