Abstract
The attitude and size of satellite targets are essential information for their activity analysis. This article proposes a novel approach to estimate the absolute attitude and size of satellite targets in the 3-D stable coordinates based on inverse synthetic aperture radar (ISAR) image interpretation. In an ISAR image of a satellite, the satellite’s body is chosen as an individual structure segmented from each ISAR image by employing pix2pix generative adversarial network (Pix2pixGAN). By exploring the shape feature of the satellite body with principal component analysis (PCA), the satellite attitude and size are estimated jointly through solving an optimization based on the gradient iteration method. The optimization is established by bridging range-Doppler (RD) images and the target feature parameters (attitude and size) with the accommodation of target trajectory information and the ISAR geometric projection model. In the experiments, the simulation data are generated from real satellite orbital parameters and the computer-aided-design (CAD) models of two satellite targets: TianGong (TG) and KeyHole (KH). Compared with the factorization-based reconstruction method, the proposed method can estimate the attitude and size of the satellite simultaneously and has a higher size estimation accuracy.
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