Three-Dimensional Imaging Method for Concealed Human Targets Based on Array Stitching

QIU Chen; CHEN Jiahui; SHAO Fengzhi; LI Nian; XU Zihan; GUO Shisheng; CUI Guolong

doi:10.11999/JEIT250334

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QIU Chen, CHEN Jiahui, SHAO Fengzhi, LI Nian, XU Zihan, GUO Shisheng, CUI Guolong. Three-Dimensional Imaging Method for Concealed Human Targets Based on Array Stitching[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250334

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QIU Chen, CHEN Jiahui, SHAO Fengzhi, LI Nian, XU Zihan, GUO Shisheng, CUI Guolong. Three-Dimensional Imaging Method for Concealed Human Targets Based on Array Stitching[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250334

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Three-Dimensional Imaging Method for Concealed Human Targets Based on Array Stitching

doi: 10.11999/JEIT250334 cstr: 32379.14.JEIT250334

School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Funds: The National Natural Science Foundation of China (62371110), China Postdoctoral Science Foundation (2023M740527), Postdoctoral Innovation Talent Support Program (BX20230056)

Received Date: 2025-04-29
Rev Recd Date: 2025-07-10

Available Online: 2025-09-16

Abstract

Abstract

Objective Traditional Through-the-Wall Radar (TWR) systems based on planar multiple-input multiple-output arrays often face high hardware complexity, calibration challenges, and increased system cost. To overcome these limitations, we propose a Three-Dimensional (3D) imaging framework based on array stitching. The method uses either time-sequential or simultaneous operation of multiple small-aperture radar sub-arrays to emulate a large aperture. This strategy substantially reduces hardware complexity while maintaining accurate 3D imaging of concealed human targets. Methods The proposed framework integrates three core techniques: 3D weighted total variation (3DWTV) reconstruction, Lucy–Richardson (LR) deconvolution, and 3D wavelet transform (3DWT)-based fusion. Radar echoes are first collected from horizontally and vertically distributed sub-arrays that emulate a planar aperture. Each sub-array image is independently reconstructed using 3DWTV, which enforces spatial sparsity to suppress noise while preserving structural details. The horizontal and vertical images are then multiplicatively fused to jointly recover azimuth and elevation information. To reduce diffraction-induced blurring, LR deconvolution models system degradation through the Point Spread Function (PSF) and iteratively refines scene reflectivity, thereby enhancing cross-range resolution. Finally, 3DWT decomposes the images into multi-scale sub-bands (e.g., LLL, LLH, LHL), which are selectively fused using absolute-maximum and fuzzy-logic rules. The inverse wavelet transform is then applied to reconstruct the final 3D image, retaining both global and local features. Results and Discussions The proposed method is evaluated through both simulations and real-world experiments using a Stepped-Frequency Continuous-Wave (SFCW) radar operating from 1.6 to 2.2 GHz with a 2Tx–4Rx configuration. In simulations, compared with baseline algorithms such as Back-Projection (BP) and the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA), the proposed method achieves better performance. Image Entropy (IE) decreases from 9.7125 for BP and 9.7065 for FISTA to 8.0711, which reflects improved image quality. Experimental tests conducted in indoor environments further confirm robustness. For both standing and sitting postures, IE is reduced from 9.9982 to 7.0030 and from 9.9947 to 6.2261, respectively. Conclusions This study presents a low-cost, high-resolution 3D imaging method for TWR systems based on array stitching. By integrating 3DWTV reconstruction, LR deconvolution, and 3DWT fusion, the method effectively reconstructs concealed human postures using a limited aperture. The approach simplifies hardware design, reduces system complexity, and preserves imaging quality under sparse sampling, thereby providing a practical solution for portable and scalable TWR systems.
- 3D imaging of concealed human targets,
- array stitching,
- 3D weighted total variation,
- Lucy–Richardson (LR) deconvolution,
- 3D wavelet transform

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References(30)

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