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

Abstract—The use of WiFi signals for human sensing has gained significant interest over the past decade. Such tech- niques provide affordable and reliable solutions for healthcare- focused event detection such as prevention of falls and long- term 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 direct- comparison 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.