다수의 IR-UWB 레이다를 이용한 인원수 및 좌표 추정 연구
People Counting and Coordinate Estimation Using Multiple IR-UWB Radars
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초록
In this paper, we propose an efficient method for estimating the number of people and their locations using multiple IR-UWB radar sensors. Using three IR-UWB radar sensors in the indoor space, the measured signal from the target is processed to remove the clutter using rejection methods. Then, to further remove the clutter and to determine the presence of the human, the time-frequency image representing the micro-Doppler is obtained and classified by a convolutional neural network. Finally, the system finds the number of human objects and estimates each position in a two-dimensional space. In experiments using the measured data, the system successfully estimated the location and number of individuals with a high accuracy ≈ 88.68 %.
Abstract
In this paper, we propose an efficient method for estimating the number of people and their locations using multiple IR-UWB radar sensors. Using three IR-UWB radar sensors in the indoor space, the measured signal from the target is processed to remove the clutter using rejection methods. Then, to further remove the clutter and to determine the presence of the human, the time-frequency image representing the micro-Doppler is obtained and classified by a convolutional neural network. Finally, the system finds the number of human objects and estimates each position in a two-dimensional space. In experiments using the measured data, the system successfully estimated the location and number of individuals with a high accuracy ≈ 88.68 %.
참고문헌 (8)
- J. H. Choi, "Learning-Based People Counting System Using an IR-UWB Radar Sensor", The Journal of Korean Institute of Electromagnetic Engineering and Science, 30(1), pp.28~37 (2019)
- J. M. Yang, "A Study on Receiving Beam Pointing Error and MTI(Moving Target Indication)Performance in a Bistatic Radar Using Pulse Chasing", The Journal of Korean Institute of Electromagnetic Engineering and Science, 21(12), pp.1412~1422 (2010)
- J. S. Lee, "Development of Doppler Processing Analysis Simulator for Radar Target Detection", Autumn Annual Conference of IEIE, pp.327~328 (2018)
- J. M. . Choi, "Automatic Censoring Cell Average(ACCA)Ordered Data Moving Average(ODMA)CFAR Detector Robust to Multiple Interference Target Environments", The Journal of Korean Institute of Communications and Information Sciences, 43(1), pp.7~15 (2018)
- B. R. Mahafza, "Radar Systems Analysis and Design Using MATLAB", pp.2000, Champman & Hall
- K. Abratkiewicz, "Multipath Interference Removal in Receivers of Linear Frequency Modulated Radar Pulses", IEEE Sensors Journal, 21(17), pp.19000~19012 (2021)
- S. Tomazic, "A Fast Recursive STFT Algorithm", MELECON 96, 2, pp.1025~1028 (1996)
- K. He, "Deep Residual Learning for Image Recognition", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.770~778 (2016)