Three-Dimensional Geometry Reconstruction Method for Slowly Rotating Space Targets Utilizing ISAR Image Sequence

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2022-03, Vol.14 (5), p.1144
• Main Authors: Zhou, Zuobang, Liu, Lei, Du, Rongzhen, Zhou, Feng
• Format: Article
• Language: English
• Subjects: Algorithms; CAD; Computer aided design; Forecasting; Geometry; Image reconstruction; Inverse synthetic aperture radar; inverse synthetic aperture radar image sequence; Mathematical models; Methods; Parameters; Particle swarm optimization; quantum-behaved particle swarm optimization; Radar imaging; Radar systems; Remote sensing; Rotation; Satellites; slowly rotating space targets; Space surveillance; Surveillance; three-dimensional geometry reconstruction
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14051144

For a slowly rotating space target (SRST) with a fixed axis, traditional 3D geometry reconstruction methods become invalid as the projection vectors cannot be formed without accurate target rotational parameters. To tackle this problem, we present a new technique for 3D geometry reconstruction by using inverse synthetic aperture radar (ISAR) image sequence energy accumulation (ISEA). Firstly, by constituting the motion model of SRST, an explicit expression is derived to describe the relative geometric relationship between the 3D geometry and ISAR image sequence. Then accurate rotational parameters and the 3D geometry of SRST can be estimated by combining the idea of the ISEA method and quantum-behaved particle swarm optimization (QPSO). Compared with the ISEA method, which can be only applied to triaxial stabilized space targets, the proposed method can achieve 3D geometry reconstruction of SRST. Experimental results based on the simulated point model and simulated electromagnetic computer aided design (CAD) model validate the effectiveness and robustness of the proposed method.