Paper Info
Title
3dried: A High-Resolution 3-D Millimeter-Wave Radar Dataset Dedicated To Imaging And Evaluation
Abstract
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 512x512x6. 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 x 2.8 mm x 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.
Year
DOI
Venue
2021
10.3390/rs13173366
REMOTE SENSING
Keywords
DocType
Volume
millimeter-wave (MMW) radar, 3-D imaging, high-resolution imaging, radar dataset, near-field
Journal
13
Issue
Citations 
PageRank 
17
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Shunjun Wei1148.82
Zichen Zhou202.70
Mou Wang303.38
Jinshan Wei401.01
Shan Liu521.05
Jun Shi62713.21
Xiaoling Zhang7124.53
Fan Fan801.35