Adaptive ADMM-Based High-Quality Fast Imaging Algorithm for Short-Range MMW MIMO-SAR Systems

Chen, Xu; Yang, Qi; Wang, Hongqiang; Zeng, Yang; Deng, Bin

doi:10.1109/tap.2023.3308963

Cited by 7 publications

(3 citation statements)

References 39 publications

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“…In recent years, due to the increasing emphasis on public safety, millimeter wave (MMW) imaging systems [1][2][3] have gradually become a necessary screening technique. Traditional security screening techniques, which mainly include X-ray machines and metal detectors, have different limitations.…”

Section: Introductionmentioning

confidence: 99%

“…However, as illustrated in Figure 1, achieving the high-precision detection of suspicious objects in MMW images faces the following challenges [4][5][6]: (1) Compared with optical images, MMW images suffer from low-resolution problems. (2) Current MMW images are actually three-channel grayscale images, so they cannot provide enough information to find statistically significant differences between suspicious items and the human body. (3) The size gaps among suspicious items are large, and there are a variety of small targets in MMW images.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Dimensional Information Fusion You Only Look Once Network for Suspicious Object Detection in Millimeter Wave Images

Chen,

Tian,

Xiong

et al. 2024

Electronics

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Millimeter wave (MMW) imaging systems have been widely used for security screening in public places due to their advantages of being able to detect a variety of suspicious objects, non-contact operation, and harmlessness to the human body. In this study, we propose an innovative, multi-dimensional information fusion YOLO network that can aggregate and capture multimodal information to cope with the challenges of low resolution and susceptibility to noise in MMW images. In particular, an MMW data information aggregation module is developed to adaptively synthesize a novel type of MMW image, which simultaneously contains pixel, depth, phase, and diverse signal-to-noise information to overcome the limitations of current MMW images containing consistent pixel information in all three channels. Furthermore, this module is capable of differentiable data enhancements to take into account adverse noise conditions in real application scenarios. In order to fully acquire the augmented contextual information mentioned above, we propose an asymptotic path aggregation network and combine it with YOLOv8. The proposed method is able to adaptively and bidirectionally fuse deep and shallow features while avoiding semantic gaps. In addition, a multi-view, multi-parameter mapping technique is designed to enhance the detection ability. The experiments on the measured MMW datasets validate the improvement in object detection using the proposed model.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-Dimensional Information Fusion You Only Look Once Network for Suspicious Object Detection in Millimeter Wave Images

Chen,

Tian,

Xiong

et al. 2024

Electronics

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show abstract

“…In recent years, many microwave and millimeter-wave (mm-wave) imaging technologies have emerged to cater to a multitude of applications based on the principles of synthetic aperture radar (SAR). These innovative applications span various domains such as nondestructive testing and evaluation (NDT&E) [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ], security inspection [ 8 , 9 , 10 , 11 , 12 , 13 ], and medical imaging [ 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. Revolutionizing aerial surveillance, small unmanned aerial vehicles (UAVs) emerge as pivotal players in SAR imaging [ 21 , 22 , 23 , 24 , 25 , 26 ].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Synthetic Aperture Radar Imaging with Random Sampling Employing Scattered Power Mapping

Kazemivala,

Nikolova

2024

Sensors

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A novel image-reconstruction method is proposed for the processing of data acquired at random spatial positions. The images are reconstructed and updated in real time concurrently with the measurements to produce an evolving image, the quality of which is continuously improving and converging as the number of data points increases with the stream of additional measurements. It is shown that the images converge to those obtained with data acquired on a uniformly sampled surface, where the sampling density satisfies the Nyquist limit. The image reconstruction employs a new formulation of the method of scattered power mapping (SPM), which first maps the data into a three-dimensional (3D) preliminary image of the target on a uniform spatial grid, followed by fast Fourier space image deconvolution that provides the high-quality 3D image.

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An Equalized ADMM-Based High-Resolution Autofocusing Imaging Algorithm for THz-SAR Ground Moving Targets

Qin,

Deng,

Wang

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Terahertz (THz) radar is well-suited for dynamic mobile target surveillance due to its high frame rates, minimal delay, and superior resolution. However, the defocusing problem caused by the motion of targets in the scene and the nonideal motion of the airborne platform severely affect synthetic aperture radar (SAR) imaging, particularly in the THz wave band. To address this issue, this paper proposes a high-resolution imaging algorithm for THz-SAR ground-moving targets using the equalized alternating direction method of multipliers (ADMM). First, the range-Doppler algorithm (RDA) is employed to generate a coarse image and extract the moving target region as the region of interest (ROI). Then the range profile can be obtained by applying the inverse fast Fourier transform (IFFT), which serves as input for the ADMM solving algorithm. Finally, the 2D image of the target is reconstructed iteratively. The algorithm fully exploits the low-rank and sparse characteristics of moving targets in the SAR image to separate them from the background. It updates the azimuthal matched filter iteratively by minimizing image entropy and designs the equalization factor to retain target details while maintaining image sparsity. This approach significantly improves focusing accuracy compared to conventional algorithms while maintaining high imaging speed without estimating Doppler parameters.

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Adaptive ADMM-Based High-Quality Fast Imaging Algorithm for Short-Range MMW MIMO-SAR Systems

Cited by 7 publications

References 39 publications

Multi-Dimensional Information Fusion You Only Look Once Network for Suspicious Object Detection in Millimeter Wave Images

Multi-Dimensional Information Fusion You Only Look Once Network for Suspicious Object Detection in Millimeter Wave Images

Real-Time Synthetic Aperture Radar Imaging with Random Sampling Employing Scattered Power Mapping

An Equalized ADMM-Based High-Resolution Autofocusing Imaging Algorithm for THz-SAR Ground Moving Targets

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