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Hand gesture recognition based on SIMO Doppler radar sensors

Hand gesture recognition based on SIMO Doppler radar sensors

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Computer-based hand gesture recognition (HGR) remains a technical challenge due to complicated image processing algorithms and excessive occupation of computational resources. Recently, wireless sensing and detection based on continuous-wave (CW) Doppler radar sensors (DRSs) have been intensively investigated, based on which experimental HGRs implemented with cost-effective, miniaturized hardware and linearized, highly efficient algorithms have been experimentally demonstrated. This DRS-based solution is able to recognize definitive, meaningful signatures of human gestures retrieved from low-sampling-rate data, exhibiting promising potential for practical applications. This chapter aims to introduce this progress. The content mainly includes an introduction to the basis of Doppler radar sensing, the architecture, and algorithms suitable for HGRs, and experimental HGR demonstrations based on such architecture and algorithms.

Chapter Contents:

  • 4.1 Doppler radar sensing
  • 4.2 Architecture
  • 4.2.1 Optimal architecture for HGR application
  • 4.2.2 SIMO-structured CW DRS
  • 4.2.3 Experimental implementation of a digital-IF DRS
  • 4.3 Algorithms
  • 4.3.1 Algorithms for the linear retrieval of Doppler signals
  • 4.3.1.1 Dynamic DC offset tracking
  • 4.3.1.2 Linearized arctangent algorithm
  • 4.3.2 Algorithms for HGRs based on a SIMO DRS
  • 4.3.2.1 2-D motion tracking algorithm
  • 4.3.2.2 3-D motion tracking algorithm
  • 4.3.2.3 Motion separation algorithm
  • 4.3.2.4 Localization with a redundant SIMO DRS
  • 4.3.2.5 Micro-Doppler analysis
  • 4.4 Experimental demonstration
  • 4.4.1 Linear retrieval of large-scale 2-D motions
  • 4.4.2 Reconstruction of 2-D gesture patterns
  • 4.4.3 Separation of interfering Doppler signal
  • 4.5 Summary
  • References

Inspec keywords: CW radar; Doppler radar; gesture recognition

Other keywords: DRS-based solution; computer-based hand gesture recognition; human-machine interface; human gestures; SIMO Doppler radar sensors; continuous-wave Doppler radar sensors

Subjects: Radar equipment, systems and applications

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