A 3‐D Shape Reconstruction Strategy for Small Solar System Bodies With Single Flyby Spaceborne Radar. Issue 4 (4th April 2023) - Hu, Chaoran; Wei, Mingchuan; Huang, Jiahe; Zhao, Yuhao; Cao, Xibin
Abstract: This article presents a novel 3‐D shape reconstruction strategy for small solar system bodies using spaceborne radar which is applied in flyby trajectories to characterize multiple targets in one mission to save time and cost. In this study, we establish a measurement geometry for rapidly spinning small solar system bodies that combines the motion properties of synthetic aperture radar and circular synthetic aperture radar techniques. We also propose a modified imaging algorithm, which is processed using Cardano's formula and the modified polar format algorithm, to improve the imaging quality. Finally, we present simulated results of point‐scattering and 3D shape models. Our analysis shows that the shape reconstruction errors of the algorithm are less than 1.5 m as indicated by the standard deviation. Plain Language Summary: Exploring small solar system bodies is crucial to understanding the evolution of our solar system. However, most of these small bodies are distant from Earth, and the small size, weak gravity, irregular shape, and high speed rotation further increase the difficulty of exploring a small solar system body. To tackle these challenges and characterize as many targets as possible in one mission, we propose a novel 3‐D imaging strategy. Our approach aims to reconstruct the 3D shape of rapidly spinning small solar system bodies in flyby trajectories. We begin by establishing an observation model and analyzing the imaging geometry and signal characteristics. Next, we describe our reconstruction procedure in detail and propose a modified algorithm to improve the imaging quality. Finally, we present simulated results to validate our proposed method. Key Points: A new three‐dimensional shape reconstruction strategy is presented for rapidly spinning small solar system bodies in flyby missions A modified imaging algorithm to compensate the phase errors to optimize the image quality is provided