Near-Field 3-D Millimeter-Wave Imaging Using MIMO RMA With Range Compensation

Wang, Zhongmin; Guo, Qijia; Tian, Xianzhong; Cui, Hong‐Liang

doi:10.1109/tmtt.2018.2884409

Cited by 77 publications

(56 citation statements)

References 25 publications

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“…Using the maximum likelihood (ML) estimation criterion, the scattering property can be estimated by using Equation (21). CSA transforms the 3-D radar imaging problem into the optimization problem in the complex domain and completes 3-D radar imaging.…”

Section: Compressed Sensing Algorithmmentioning

confidence: 99%

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3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation

et al. 2021

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Millimeter-wave (MMW) 3-D imaging technology is becoming a research hotspot in the field of safety inspection, intelligent driving, etc., due to its all-day, all-weather, high-resolution and non-destruction feature. Unfortunately, due to the lack of a complete 3-D MMW radar dataset, many urgent theories and algorithms (e.g., imaging, detection, classification, clustering, filtering, and others) cannot be fully verified. To solve this problem, this paper develops an MMW 3-D imaging system and releases a high-resolution 3-D MMW radar dataset for imaging and evaluation, named as 3DRIED. The dataset contains two different types of data patterns, which are the raw echo data and the imaging results, respectively, wherein 81 high-quality raw echo data are presented mainly for near-field safety inspection. These targets cover dangerous metal objects such as knives and guns. Free environments and concealed environments are considered in experiments. Visualization results are presented with corresponding 2-D and 3-D images; the pixels of the 3-D images are 512×512×6. In particular, the presented 3DRIED is generated by the W-band MMW radar with a center frequency of 79GHz, and the theoretical 3-D resolution reaches 2.8 mm × 2.8 mm × 3.75 cm. Notably, 3DRIED has 5 advantages: (1) 3-D raw data and imaging results; (2) high-resolution; (3) different targets; (4) applicability for evaluation and analysis of different post processing. Moreover, the numerical evaluation of high-resolution images with different types of 3-D imaging algorithms, such as range migration algorithm (RMA), compressed sensing algorithm (CSA) and deep neural networks, can be used as baselines. Experimental results reveal that the dataset can be utilized to verify and evaluate the aforementioned algorithms, demonstrating the benefits of the proposed dataset.

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Section: Compressed Sensing Algorithmmentioning

confidence: 99%

“…However, when the number of array elements is large, the computing efficiency will be lost. Therefore, the range migration algorithm (RMA) [20,21], which is a more efficient algorithm, has emerged. RMA uses fast Fourier transform (FFT) and matrix multiplication in the frequency domain to complete imaging.…”

Section: Introductionmentioning

confidence: 99%

3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation

et al. 2021

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“…Let us denote the location of the phase center associated with the transmitter element at (x + ∆ T /2, y T , Z 0 ) and the receiver element at (x − ∆ T /2, y R , Z 0 ) as (x , y , Z 0 ). Defining a reference point (x 0 , y 0 , z 0 ) in the target domain, the received multistatic data set s(x , y T , y R , k) can be converted to the effective monostatic version as [41], [42]…”

Section: B Range Migration Algorithm For Mimo-sarmentioning

confidence: 99%

“…The range migration algorithm (RMA) using Fourier-based inversion methods is the most efficient and widely used approach in conventional monostatic SAR imaging for both planar [6], [39] and cylindrical/spherical [29], [40] scanning geometries. In order to extend the RMA to MIMO-SAR configurations, we adopt a multistatic-to-monostatic conversion approach proposed in [41], [42] to transform the multistatic array topology into a monostatic format according to the equivalent phase center principle based on a reference point on the target. On the other hand, the multistatic-to-monostatic conversion technique used in the RMA is precise only for the selected reference point.…”

Section: Introductionmentioning

confidence: 99%

Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

2020

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Multiple-input multiple-output (MIMO) radars and synthetic aperture radar (SAR) techniques are well researched and have been effectively combined for many imaging applications ranging from remote sensing to security. Despite numerous studies that apply MIMO concepts to SAR imaging, the design process of a MIMO-SAR system is non-trivial, especially for millimeter-wave (mmWave) imaging systems. Many issues have to be carefully addressed. Besides, compared with conventional monostatic sampling schemes or MIMO-only solutions, efficient image reconstruction methods for MIMO-SAR topologies are more complicated in short-range applications. To address these issues, we present highly-integrated and reconfigurable MIMO-SAR testbeds, along with examples of three-dimensional (3-D) image reconstruction algorithms optimized for MIMO-SAR configurations. The presented testbeds utilize commercially available wideband mmWave sensors and motorized rail platforms. Several aspects of the MIMO-SAR testbed design process, including MIMO array calibration, electrical/mechanical synchronization, system-level verification, and performance evaluation, are described. We present three versions of MIMO-SAR testbeds with different implementation costs and accuracies to provide alternatives for other researchers who want to implement their testbed framework. Several representative examples in various real-world imaging applications are presented to demonstrate the capabilities of the proposed testbeds and algorithms. INDEX TERMS Millimeter-wave (mmWave) radar, multiple-input multiple-output (MIMO) radar, synthetic aperture radar (SAR), frequency-modulated continuous-wave (FMCW), back projection algorithm (BPA), range migration algorithm (RMA), three-dimensional (3-D) imaging, testbed design, calibration.

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“…Firstly, taking single-frequency holography as an example, the millimeter-wave wavelength is λ, the wave number k = 2π/λ and the target complex reflectivity is f (x, y) [10,11]. Based on plane scanning, R x is the omnidirectional antenna, transceiver antenna T x , R x are in the same position (x 0 , y 0 ), the vertical distance between the target plane and the scanning plane is set as z 0 , the distance between the object point (x, y) and the transceiver antenna position (x 0 , y 0 ) is as follows:…”

Section: Accurate Millimeter-wave Reconstruction Algorithm Based On Spherical Wave Expansionmentioning

confidence: 99%

Accurate Imaging of Wide Beam Active Millimeter Wave Based on Angular Spectrum Theory and Simulation Verification

2021

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Due to the fact that a millimeter-wave (MMW) has a strong ability to penetrate clothing, MMW holographic imaging technology can conduct a non-contact inspection of the human body’s surface. In recent years, personnel surveillance systems utilizing MMW holographic imaging technology has achieved rapid progress. However, limited by MMW holographic imaging’s image quality, the existing imaging technology cannot accurately detect whether the human body carries hidden objects. Additionally, real-time inspection requirements cannot be practically satisfied, and the system cost is relatively high. In this paper, a reconstruction algorithm with enhanced imaging quality, which can solve the problem of spherical wave attenuation with distance, making imaging results more accurate. The sampling conditions and imaging resolution are simulated and analyzed, which verify the azimuth resolution. Furthermore, the antenna beam’s holographic imaging simulation is optimized, effectively improving the quality of the reconstructed image. The proposed scheme provides theoretical support for determining antenna step and scanning aperture size in engineering and have theoretical guiding significance for improving the image quality of millimeter-wave holography and reducing system cost.

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Near-Field 3-D Millimeter-Wave Imaging Using MIMO RMA With Range Compensation

Cited by 77 publications

References 25 publications

3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation

3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation

Development and Demonstration of MIMO-SAR mmWave Imaging Testbeds

Accurate Imaging of Wide Beam Active Millimeter Wave Based on Angular Spectrum Theory and Simulation Verification

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