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Article

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

1
School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2
Science and Technology on Communication Security Laboratory, Institute of Southwestern Communication, Chengdu 610041, China
*
Author to whom correspondence should be addressed.
Academic Editors: Lingli Zhu, Jonathan Li and Sylvie Daniel
Remote Sens. 2021, 13(17), 3366; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13173366
Received: 22 July 2021 / Revised: 20 August 2021 / Accepted: 23 August 2021 / Published: 25 August 2021
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. View Full-Text
Keywords: millimeter-wave (MMW) radar; 3-D imaging; high-resolution imaging; radar dataset; near-field millimeter-wave (MMW) radar; 3-D imaging; high-resolution imaging; radar dataset; near-field
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MDPI and ACS Style

Wei, S.; Zhou, Z.; Wang, M.; Wei, J.; Liu, S.; Shi, J.; Zhang, X.; Fan, F. 3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation. Remote Sens. 2021, 13, 3366. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13173366

AMA Style

Wei S, Zhou Z, Wang M, Wei J, Liu S, Shi J, Zhang X, Fan F. 3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation. Remote Sensing. 2021; 13(17):3366. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13173366

Chicago/Turabian Style

Wei, Shunjun, Zichen Zhou, Mou Wang, Jinshan Wei, Shan Liu, Jun Shi, Xiaoling Zhang, and Fan Fan. 2021. "3DRIED: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated to Imaging and Evaluation" Remote Sensing 13, no. 17: 3366. https://0-doi-org.brum.beds.ac.uk/10.3390/rs13173366

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