Multi-projection Plane InISAR 3D Reconstruction Method for Complex Moving Ship Targets

LI Ning; NIU Jinfa; WANG Weibin; HU Xingwang; WU Lin

doi:10.11999/JEIT251268

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LI Ning, NIU Jinfa, WANG Weibin, HU Xingwang, WU Lin. Multi-projection Plane InISAR 3D Reconstruction Method for Complex Moving Ship Targets[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT251268

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LI Ning, NIU Jinfa, WANG Weibin, HU Xingwang, WU Lin. Multi-projection Plane InISAR 3D Reconstruction Method for Complex Moving Ship Targets[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT251268

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Multi-projection Plane InISAR 3D Reconstruction Method for Complex Moving Ship Targets

doi: 10.11999/JEIT251268 cstr: 32379.14.JEIT251268

LI Ning^{1, 2, 3
,
,},
NIU Jinfa^{1, 2, 3},
WANG Weibin⁴,
HU Xingwang⁴,
WU Lin^{1, 2, 3}

1.
School of Computer and Information Engineering, Henan University, Kaifeng 475004, China
2.
Henan Key Laboratory of Big Data Analysis and Processing, Kaifeng 475004, China
3.
Henan Province Engineering Research Center of Spatial Information Processing, Kaifeng 475004, China
4.
School of Electronics and Communication Engineering, Sun Yat-Sen University, Shenzhen 518107, China

Funds: Natural Science Foundation of Henan under Grant (242300421170)

Received Date: 2025-12-01
Accepted Date: 2026-03-09
Rev Recd Date: 2026-03-09

Available Online: 2026-03-16

Abstract

Abstract

Objective Interferometric Inverse Synthetic Aperture Radar (InISAR) is a three-dimensional (3D) reconstruction technique for non-cooperative targets. However, the complex 3D rotational motion of ship targets causes unstable Doppler frequency variation. Inverse Synthetic Aperture Radar (ISAR) imaging also inevitably suffers from target overlap and occlusion. These factors make high-precision and complete 3D reconstruction under a single projection plane difficult. Therefore, a multi-projection plane InISAR 3D reconstruction method for complex moving ship targets based on point cloud fusion is proposed. The method supplements target 3D information through efficient and high-precision point cloud registration and fusion, thereby significantly improving 3D reconstruction quality. Methods This method fully exploits the advantage of multi-plane observation enabled by the severe motion of ship targets. The ship centerline is extracted, and the vertical rotation vector is estimated by Principal Component Analysis (PCA) to select the optimal imaging times corresponding to different Imaging Projection Planes (IPPs). ISAR imaging and InISAR 3D reconstruction are then completed. In addition, a point cloud fusion algorithm that combines Weighted Random Sample Consensus (RANSAC) and hierarchical Iterative Closest Point (ICP) is proposed. The random sampling process is optimized through a feature stability weighting strategy, which enables efficient extraction and matching of corresponding feature points in InISAR images and achieves high-precision point cloud fusion under multiple IPPs. Results and Discussions Experimental results show that the proposed method significantly improves reconstruction accuracy and target completeness. For simulated ship point-target data, Fig. 7 shows excellent results, with a significant reduction in reconstruction error. Signal-to-Noise Ratio (SNR) analysis shows that the quality of 3D fusion imaging improves steadily as the SNR increases from –10 dB to 10 dB, and robust fusion performance is maintained even under low-SNR conditions. For simulated destroyer Radar Cross Section (RCS) data, the method achieves strong registration performance. The detail recovery and structural integrity of the fused image are also significantly improved, effectively addressing the incomplete reconstruction of 3D information caused by scattering-point overlap and occlusion. Conclusions To address the low reconstruction accuracy and information loss caused by target rotation, overlap, and occlusion in traditional InISAR methods for 3D reconstruction of complex moving ship targets, a multi-IPP InISAR 3D reconstruction method based on point cloud fusion is proposed. The method uses a PCA-based optimal imaging time selection strategy. Weighted RANSAC and hierarchical ICP algorithms are then applied to achieve efficient and high-precision registration and fusion of InISAR point clouds under multiple IPPs, thereby producing high-quality 3D reconstruction results. Multi-scenario experiments are conducted by constructing both a ship model with ideal scattering points and an electromagnetic simulation RCS model with occlusion effects. The results verify the accuracy of the proposed method under ideal conditions and demonstrate its applicability in complex real-world scenarios.
- ISAR imaging,
- InISAR reconstruction,
- Ship target,
- Multi-projection plane,
- RANSAC-ICP

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References(22)

References

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