Multi-plane Sparse MIMO Array for Millimeter Wave Imaging

Xing, Guangnan; Wang, Shuoguang; Jing, Handan; Li, Shiyong

doi:10.1109/icmmt55580.2022.10022402

Cited by 1 publication

(2 citation statements)

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“…The maximum learning rate is set as 0.0001, and the minimum learning rate is set as 0.01 of the maximum learning rate. For the setting of anchor_size, this experiment is set to [8,16,32], with each number corresponding to three prior boxes, resulting in nine prior boxes for each feature point. According to this setting, the generated prior box widths and heights are reported in the following:…”

Section: Seating Situationmentioning

confidence: 99%

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Vehicle Occupant Detection Based on MM-Wave Radar

Li,

Wang,

Wang

2024

Sensors

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With the continuous development of automotive intelligence, vehicle occupant detection technology has received increasing attention. Despite various types of research in this field, a simple, reliable, and highly private detection method is lacking. This paper proposes a method for vehicle occupant detection using millimeter-wave radar. Specifically, the paper outlines the system design for vehicle occupant detection using millimeter-wave radar. By collecting the raw signals of FMCW radar and applying Range-FFT and DoA estimation algorithms, a range–azimuth heatmap was generated, visually depicting the current status of people inside the vehicle. Furthermore, utilizing the collected range–azimuth heatmap of passengers, this paper integrates the Faster R-CNN deep learning networks with radar signal processing to identify passenger information. Finally, to test the performance of the detection method proposed in this article, an experimental verification was conducted in a car and the results were compared with those of traditional machine learning algorithms. The findings indicated that the method employed in this experiment achieves higher accuracy, reaching approximately 99%.

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Section: Seating Situationmentioning

confidence: 99%

“…In short, radar systems have the advantages of high integration, low cost, and low power consumption, and they are not affected by weather conditions and do not infringe on personal privacy [16]. Therefore, using radar as a sensor can provide reliable and accurate detection for passengers in vehicle environments.…”

mentioning

confidence: 99%