PP-ISEA: An Efficient Algorithm for High-Resolution Three-Dimensional Geometry Reconstruction of Space Targets Using Limited Inverse Synthetic Aperture Radar Images
Rundong Wang, Weigang Zhu, Chenxuan Li, Bakun Zhu, Hongfeng Pang
TL;DR
This paper introduces PP-ISEA, a new method for efficiently reconstructing 3D geometry of space targets using fewer radar images.
Contribution
PP-ISEA improves 3D reconstruction efficiency by using a two-step search and a novel objective function requiring fewer images.
Findings
PP-ISEA reduces the minimum image requirement from ten to four for high-quality reconstruction.
The method achieves superior reconstruction quality with less computational time.
Experiments confirm improved efficiency and accuracy using scatterer and electromagnetic models.
Abstract
As the variety of space targets expands, two-dimensional (2D) ISAR images prove insufficient for target recognition, necessitating the extraction of three-dimensional (3D) information. The 3D geometry reconstruction method utilizing energy accumulation of ISAR image sequence (ISEA) facilitates superior reconstruction while circumventing the laborious steps associated with factorization methods. Nevertheless, ISEA’s neglect of valid information necessitates a high quantity of images and elongated operation times. This paper introduces a partitioned parallel 3D reconstruction method utilizing sorted-energy semi-accumulation with ISAR image sequences (PP-ISEA) to address these limitations. The PP-ISEA innovatively incorporates a two-step search pattern—coarse and fine—that enhances search efficiency and conserves computational resources. It introduces a novel objective function…
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Taxonomy
TopicsAdvanced SAR Imaging Techniques · Synthetic Aperture Radar (SAR) Applications and Techniques · Robotics and Sensor-Based Localization