Remote Sensing (Nov 2022)

A Framework for Distributed LEO SAR Air Moving Target 3D Imaging via Spectral Estimation

  • Yaquan Han,
  • Runzhi Jiao,
  • Haifeng Huang,
  • Qingsong Wang,
  • Tao Lai

DOI
https://doi.org/10.3390/rs14235956
Journal volume & issue
Vol. 14, no. 23
p. 5956

Abstract

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This paper aims to perform imaging and detect moving targets in a 3D scene for space-borne air moving target indication (AMTI). Specifically, we propose a feasible framework for distributed LEO space-borne SAR air moving target 3D imaging via spectral estimation. This framework contains four subsystems: the distributed LEO satellite and radar modeling, moving target information processing, baseline design framework, and spectrum estimation 3D imaging. Firstly in our method, we develop a relative motion model between the satellite platform and the 3D moving target for satellite and radar modeling. In a very short time, the relative motion between the platform and the target is approximated as a uniform motion. We then establish the space-borne distributed SAR moving target 3D imaging model based on the motion model. After that, we analyze the influencing factors, including the Doppler parameters, the three-dimensional velocity, acceleration, and baseline intervals, and further investigate the performance of the 3D imaging of the moving target. The moving target spectrum estimation 3D imaging finally obtains the 3D imaging results of the target, which preliminarily solves the imaging and resolution problems of slow air moving targets. Simulations are conducted to verify the effectiveness of the proposed distributed LEO space-borne SAR moving target 3D imaging framework.

Keywords