Abstract
In this paper, comprehensive mPoint, a method for generating 3D (range, azimuth, and elevation) point cloud of human targets using a Frequency-Modulated Continuous Wave (FMCW) signal and Multi-Input Multi-Output (MIMO) millimeter wave radar is proposed. Distinct from the TI-mPoint method proposed by TI technology, a comprehensive mPoint method considering both the static and dynamic characteristics of radar reflected signals is utilized to generate a high precision point cloud, resulting in more comprehensive information of the target being detected. The radar possessing 60–64 GHz FMCW signal with two sets of different dimensional antennas is utilized in order to experimentally verify the results of the methodology. By using the proposed process, the point cloud data of human targets can be obtained based on six different postures of the underlying human body. The human posture cube and point cloud accuracy rates are defined in the paper in order to quantitively and qualitatively evaluate the quality of the generated point cloud. Benefitting from the proposed comprehensive mPoint, evidence shows that the point number and the accuracy rate of the generated point cloud compared with those from the popular TI-mPoint can be largely increased by 86% and 42%, respectively. In addition, the noise level of multipath reflection can be effectively reduced. Moreover, the length of the algorithm running time is only 1.6% longer than that of the previous method as a slight tradeoff.
Highlights
Published: 27 September 2021Human target detection systems are widely employed in various areas for specific purposes such as safety, healthy and energy conservation
For the application in smart vehicles, human detection technology can aid in avoiding collisions around the vehicle and provide child-left-behind warning to drivers, which enhances safety and security
In order to discuss the performance of the comprehensive mPoint, six sets of environment is same as that shown in Figure 3, and the person involved in the test stands raw data of target
Summary
Published: 27 September 2021Human target detection systems are widely employed in various areas for specific purposes such as safety, healthy and energy conservation. Conventional sensors are utilized to detect occupancy in a specific area, such as passive infrared (PIR) sensor, CO2 sensor and ultrasonic sensor [6,7,8,9] These sensors have the limitations such as sensitivity to temperature, slow response, etc. Both the azimuth and elevation angle information of the detected target from two combined RAIs are captured based on the corresponding range and SNR value in order to help generate the 3D point cloud of the target. Sensors 2021, 21, x FOR PEER REVIEW Transmit Signal Receive
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