Opportunistic Doppler-Only Indoor Localization Via Passive Radar

Li, Wenda; Tan, Bo; Piechocki, Robert J.

doi:10.1109/dasc/picom/datacom/cyberscitec.2018.00093

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…The performance of activity recognition and breathing detection is affected by the geometry of the transmitter and receivers. Passive WiFi radar for indoor localization is achieved by tracking the Doppler due to a moving object from at least two separated channels [20]. However, the localization accuracy only depends on the Doppler information which will accumulate error over time [20].…”

Section: B Passive Wifi Radarmentioning

confidence: 99%

On CSI and Passive Wi-Fi Radar for Opportunistic Physical Activity Recognition

Bocus

Chun

et al. 2022

IEEE Trans. Wireless Commun.

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The use of WiFi signals for human sensing has gained significant interest over the past decade. Such techniques provide affordable and reliable solutions for healthcarefocused event detection such as prevention of falls and longterm monitoring of chronic diseases. Currently, there are two major approaches for WiFi sensing: Passive WiFi Radar (PWR) which uses well established approaches from bistatic radar, and Channel State Information (CSI) which comes from the WiFi communication system. However, to our knowledge there has not been a comprehensive study to understand and compare both approaches in terms of their robustness and limitations for monitoring the movements of people. In this paper, we describe the fundamentals of both the CSI and PWR systems and the associated signal processing methodologies. To facilitate a directcomparison between CSI and PWR, we have implemented a monitoring system for simultaneously measuring human activity using both techniques in comparable conditions. Experimental results show that CSI system works better in line-of-sight condition, whereas PWR system works better in non-line-of-sight condition. CSI system is more sensitive to the small activities, while PWR system provides meaningful Doppler spectrograms. It is therefore recommended that a real-world future WiFi system should leverage the fusion of the two approaches.

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Section: B Passive Wifi Radarmentioning

confidence: 99%