Sequential Ground Moving Target Imaging Based on Hybrid ViSAR-ISAR Image Formation in Terahertz Band

Sequential ground moving target imaging (GMTIm) is an imperative and challenging task under terahertz video synthetic aperture radar (THz-ViSAR), which contributes to fine-grained situational awareness and moving target (MT) recognition. However, traditional GMTIm methods are usually designed for single-frame images, which involves repetitive parameter estimation for the sequential imaging problem and lacks the efficiency due to the parameter sensitivity. To tackle the aforementioned problems, this paper proposes a sequential GMTIm method based on hybrid THz-ViSAR-inverse SAR (ISAR) image formation. With respect to ViSAR processing, the sequential imaging results are firstly obtained. Considering the similarity of scene among inter-frame images, MTs can be detected based on target-level change detection after image registration and shadows left on the road. Following this, the defocused target region is transformed to obtain raw echoes, which is beneficial for parallel processing and reduce the computation amount. As for ISAR processing, the envelope alignment and auto-focus methods are employed to eliminate the residual motion errors and compensate for phase errors without constructing prior motion patterns. Thereafter, the ratio of equivalent rotational velocities between MTs and the scene is estimated to achieve the azimuth scaling. Finally, sparsity-based imaging enhancement is employed to further enhance the imaging quality. Simulations and airborne experiments are carried out to validate the effectiveness of the proposed method.

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Publication Details

Journal
IEEE Transactions on Circuits and Systems for Video Technology
Published
2025-04-01
DOI
https://doi.org/10.1109/tcsvt.2025.3556396
Citations
11
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
54.93

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article

Sequential Ground Moving Target Imaging Based on Hybrid ViSAR-ISAR Image Formation in Terahertz Band

Bin Deng, Qi Yang, Lei Fan, Yuliang Qin et al.
11 citations
IEEE Transactions on Circuits and Systems for Video Technology
Advanced SAR Imaging Techniques
54.93
article

Sequential Ground Moving Target Imaging Based on Hybrid ViSAR-ISAR Image Formation in Terahertz Band

Bin Deng, Qi Yang, Lei Fan, Yuliang Qin, Hongqiang Wang
article en
11 citations

Abstract

Sequential ground moving target imaging (GMTIm) is an imperative and challenging task under terahertz video synthetic aperture radar (THz-ViSAR), which contributes to fine-grained situational awareness and moving target (MT) recognition. However, traditional GMTIm methods are usually designed for single-frame images, which involves repetitive parameter estimation for the sequential imaging problem and lacks the efficiency due to the parameter sensitivity. To tackle the aforementioned problems, this paper proposes a sequential GMTIm method based on hybrid THz-ViSAR-inverse SAR (ISAR) image formation. With respect to ViSAR processing, the sequential imaging results are firstly obtained. Considering the similarity of scene among inter-frame images, MTs can be detected based on target-level change detection after image registration and shadows left on the road. Following this, the defocused target region is transformed to obtain raw echoes, which is beneficial for parallel processing and reduce the computation amount. As for ISAR processing, the envelope alignment and auto-focus methods are employed to eliminate the residual motion errors and compensate for phase errors without constructing prior motion patterns. Thereafter, the ratio of equivalent rotational velocities between MTs and the scene is estimated to achieve the azimuth scaling. Finally, sparsity-based imaging enhancement is employed to further enhance the imaging quality. Simulations and airborne experiments are carried out to validate the effectiveness of the proposed method.

IEEE Transactions on Circuits and Systems for Video TechnologyVol. 35(9)
National University of Defense Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 0%
Advanced SAR Imaging Techniques
54.93
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