Abstract
In this paper, a three-dimensional (3D) reconstruction algorithm is proposed for space targets with multistatic inverse synthetic aperture radar (ISAR) systems. In the proposed algorithm, target 3D geometry can be obtained by solving the projection equations between the target 3D geometry and ISAR images. Specially, it is no need to perform cross-range scaling. To obtain the projection equations, the algorithm consists of two steps: establishing projection matrix and associating scattering centers. Firstly, observation angles of sensor can be estimated by kinematic formulas and coordinate systems transformation. Using azimuth and elevation angles of sensor relative to target, the projection matrix from target 3D geometry to ISAR images is established. Secondly, an association cost function based on projective transform and epipolar geometry is developed. As the cost function is an assignment with 0–1 linear programming, the Jonker-Volgenant algorithm is used to build a one-to-one correspondence between two scattering centers. Numerical results show the efficiency of the proposed algorithm.
Highlights
For space targets, it is important to conduct identifications for these interesting components, such as cabin and solar panels in the event of their aberrancy
3 three dimensional (3D) reconstruction using two dimensional (2D) inverse synthetic aperture radar (ISAR) images Based on the signal model shown in Section 2, a 3D reconstruction algorithm is proposed for space targets with multistatic ISAR systems
4.1 Experiment 1 Here, an experiment is presented to compare the performance of the proposed association method which is defined as epipolar geometry projective (EGP) method with the nearest neighbor (NN) method, robust point matching (RPM) method [21], and coherent point drift (CPD) method [22]
Summary
It is important to conduct identifications for these interesting components, such as cabin and solar panels in the event of their aberrancy. Observation angles of sensor are estimated by using kinematic formulas and coordinate system transformation, so the projection matrix from the target 3D geometry to the trajectory of scattering centers can be build. A new method based on projective transform and epipolar geometry [12] is proposed to associate scattering centers between different images.
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