Abstract

The interferometric imaging radar altimeter (InIRA), mounted on the Tiangong-2 space laboratory, utilizes a small incidence and a short interferometric baseline to achieve altimetry for wide swathes of ocean surface topography and inland water surface elevation. To obtain a high-precision digital elevation model (DEM), calibration of the interferometric system parameters is necessary. Because InIRA utilizes the small-incidence interference system design, serious coupling occurs between the interferometric parameters. Commonly used interferometric calibration methods tend to fall into the local optimal solution for InIRA. Because evolutionary algorithms have a stronger robustness and global search ability, they are better suited to handling the solution space structure under the coupling of complex interferometric parameters. This article establishes an interferometric calibration optimization model for InIRA by utilizing the relative flatness of the lake surface as an inequality constraint. Furthermore, an adaptive penalty coefficient constraint evolutionary algorithm is designed to solve the model. The proposed method was tested on actual InIRA data, and the results indicate that it efficiently adjusts interferometric parameters, enhancing the precision of measurements for Qinghai Lake elevation.

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