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Application of the RPC model for spaceborne SAR image geometric processing

机译:RPC模型在星载SAR图像几何处理中的应用

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An increasing number of low, medium, and high resolution SAR satellites creates a demand for a generalized sensor model to replace the rigorous sensor model (RSM). The rational polynomial coefficient (RPC) model is a generic sensor model which accurately fits the object-image geometry for various sensor systems with different coefficient values. It has been widely used as an alternative to RSM for photogrammetric processing of optical images, but its applications to SAR images are rarely discussed in publications. In this paper, the feasibility and practicability of the RPC model for SAR images are studied. The RPC model can not only be used to replace the RSM (range–Doppler model for SAR), but also applied to the processing chain for SAR data, thus facilitating the processing of SAR and InSAR data for end users.
机译:低分辨率,中分辨率和高分辨率SAR卫星的数量不断增长,这就要求用通用传感器模型来代替严格的传感器模型(RSM)。有理多项式系数(RPC)模型是一种通用传感器模型,可针对具有不同系数值的各种传感器系统准确拟合对象图像几何形状。它已被广泛用作RSM的替代品,用于光学图像的摄影测量处理,但在出版物中很少讨论其在SAR图像中的应用。本文研究了SAR图像的RPC模型的可行性和实用性。 RPC模型不仅可以用来代替RSM(SAR的距离多普勒模型),而且可以应用于SAR数据的处理链,从而为最终用户提供了处理SAR和InSAR数据的便利。

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