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 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.

Three-Dimensional Sparse SAR Imaging with Generalized Lq Regularization

“…Finally, two sets of real 3D ground-based array SAR data were used to verify the effectiveness of the algorithms. The real data of the complex scene was provided by [34]. The imaging model was a 3D linear array SAR.…”

Near Field 3-D Millimeter-Wave SAR Image Enhancement and Detection with Application of Antenna Pattern Compensation

“…However, the existing literature has not thoroughly discussed the suppression of the imaging clutter or ghost due to the non-ideal electromagnetic environment or sparse arrays during the imaging process [33]. Although practical progress has been made toward the current imaging optimization algorithms, most of them are performed under darkroom conditions and are not generally applicable to security detection scenarios [34][35][36][37][38][39][40][41][42][43].…”

“…The measured results validate the robustness of the proposed algorithm in a complex environment or sparse arrays, and the analysis in the subsequent sections provides an intensive evaluation of the difference in parameter metrics between the technique and traditional imaging algorithms. Finally, we use the 3DRIED [35] to construct the image datasets under these three algorithms for practical inspection and validation. The proposed method indicates a higher fidelity focus comparable to the traditional planar RMA and BPA, even under non-ideal electromagnetic environments.…”

A Flexible Region of Interest Extraction Algorithm with Adaptive Threshold for 3-D Synthetic Aperture Radar Images

“…[15][16][17][18][19][20][21][22]. The gray levels of the 3-D SAR images that we processed [13,23,24] follow Gamma distribution. Furthermore, the algorithm proposed in this paper is based on this hypothesis.…”

“…Finally, the DPP stores the digital echo data and achieves 3-D SAR imaging. References [23,24] show two different near-field 3-D SAR imaging systems.…”