A Novel Detection and Recognition Method for Continuous Hand Gesture Using FMCW Radar

• Published in: IEEE access Vol. 8; pp. 167264 - 167275
• Main Authors: Wang, Yong, Ren, Aihu, Zhou, Mu, Wang, Wen, Yang, Xiaobo
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Classification algorithms; Clustering algorithms; continuous hand gesture recognition detection; Continuous radiation; Fast Fourier transformations; FDTW; FMCW radar; Fourier transforms; Gesture recognition; Heuristic algorithms; Parameter estimation; Radar detection; Recognition; Signal classification; Time-frequency analysis; time-frequency trajectory
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3023187

In this article, a novel method for continuous hand gesture detection and recognition is proposed based on a frequency modulated continuous wave (FMCW) radar. Firstly, we adopt the 2-Dimensional Fast Fourier Transform (2D-FFT) to estimate the range and Doppler parameters of the hand gesture raw data, and construct the range-time map (RTM) and Doppler-time map (DTM). Meanwhile, we apply the Multiple Signal Classification (MUSIC) algorithm to calculate the angle and construct the angle-time map (ATM). Secondly, a hand gesture detection method is proposed to segment the continuous hand gestures using a decision threshold. Thirdly, the central time-frequency trajectory of each hand gesture spectrogram is clustered using the <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means algorithm, and then the Fusion Dynamic Time Warping (FDTW) algorithm is presented to recognize the hand gestures. Finally, experiments show that the accuracy of the proposed hand gesture detection method can reach 96.17%. The hand gesture average recognition accuracy of the proposed FDTW algorithm is 95.83%, while its time complexity is reduced by more than 50%.