Abstract
Limitations of optical devices for motion sensing such as small coverage, sensitivity to obstacles, and privacy exposure result in the need for improvement. As motion sensing based on radio frequency signals is not constrained by the limitation above, channel state information (CSI) from Wi-Fi devices could be used to improve sensing performance under the above circumstances. Unfortunately, CSI phase cannot be practically obtained due to the temporal phase rotation generated from Wi-Fi chips. Therefore, it would be rather complicated to realize motion analysis, especially the direction of motion. To mitigate the issue, this paper proposes a CSI calibration method that employs a back-to-back channel between Wi-Fi transceivers for phase rotation removal while preserving the original CSI phase. Through experiment, calibrated CSI showed a high similarity to the channel without phase rotation measured using a Vector Network Analyzer (VNA). Another experiment was conducted to observe Doppler frequency due to simple hand gestures using the Wavelet transform. A visual analysis revealed that the Doppler frequency of calibrated CSI could correctly capture the motion pattern. To the best of the authors’ knowledge, this is the first calibration method that maintains the original CSI and is applicable for in-depth motion analysis.
Highlights
Technology in human-computer interaction (HCI) is moving toward the contactless interface where users could communicate with any computing devices by merely performing a particular gesture in the air
This paper first described how WI-Fi channel state information is estimated and the significance of spatial mapping and cyclic shift diversity to the additional shift of CSI phase which needs to be removed before further analysis
Bistatic Doppler radar model was employed to describe the effect of motion as Doppler frequency in CSI
Summary
Technology in human-computer interaction (HCI) is moving toward the contactless interface where users could communicate with any computing devices by merely performing a particular gesture in the air. Some vision-based motion sensing systems have already been commercialized such as Kinect, Leap Motion, and Orbbec These systems promise high tracking accuracy and precision, it unavoidably has to deal with the physical limitation of the optical device. It has small active sensing area which highly depends on the focal length of the lens, operates only in the presence of line-of-sight (LoS) between device and user, and might raise a concern in privacy exposure issue [1,2,3]. Leveraging commercial radio frequency (RF) system (Wi-Fi, Bluetooth, RFID, etc.)
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