Blind Separation of Doppler Human Gesture Signals Based on Continuous-Wave Radar Sensors

Zhitao Gu, Jun Wang, Fazhong Shen, Kuiwen Xu, Dexin Ye, Jiangtao Huangfu, Changzhi Li, Lixin Ran

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Recently, progresses have been made in hand gesture recognition based on Doppler radar sensors. However, it remains a technical challenge to avoid the interfering human motions. An example is detecting hand gestures in the presence of random body movements. In this paper, we propose a solution based on a Single-input Multiple-output frontend and a blind motion separation algorithm. Assisted by an additional receiving channel, Doppler signals caused by different motions can be separated by extending the algorithm originally developed for separating human voices. The experimental separation of hand gestures from interfering movements verified the effectiveness of this approach. The proposed solution can be potentially used in novel applications such as human gait and gesture recognitions.

Original languageEnglish
Article number8653471
Pages (from-to)2659-2661
Number of pages3
JournalIEEE Transactions on Instrumentation and Measurement
Issue number7
StatePublished - Jul 2019


  • Blind motion separation
  • Doppler radar sensor (DRS)
  • gesture recognition
  • independent component analysis (ICA)


Dive into the research topics of 'Blind Separation of Doppler Human Gesture Signals Based on Continuous-Wave Radar Sensors'. Together they form a unique fingerprint.

Cite this