Indoor non-rhythmic human motion classification using a frequency-modulated continuous-wave radar

• Main Authors: Yu Zou, Chuanwei Ding, Hong Hong, Changzhi Li, Xiaohua Zhu
• Format: Article
• Language: English
• Published: Wiley 2019-09-01
• Series: The Journal of Engineering
• Subjects: cw radar; feature extraction; learning (artificial intelligence); fm radar; pattern classification; doppler radar; indoor environment; echo; indoor nonrhythmic human motion classification; frequency-modulated continuous-wave radar; indoor scenario; range feature extraction; doppler feature extraction; echo signals; machine learning classifier subspace k-nearest neighbour; nonrhythmic motion recognition
• Online Access: https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0560

Human motion classification is widely used in intelligent house, surveillance, search and rescue operation, intelligent house, and elder monitoring. In this study, a frequency-modulated continuous-wave radar is utilised to classify non-rhythmic human motion in an indoor scenario. Both the range and Doppler features are extracted from echo signals for a machine learning classifier subspace K-nearest neighbour. Extensive experiments demonstrate its feasibility, and an accuracy rate of 94.2% was achieved in recognition of eight typical non-rhythmic motions.