Passive Human Trajectory Tracking Study in Indoor Environment with CSI

Device-free indoor human trajectory tracking is critical to support many applications with the elder health care. Available works mainly achieved the human trajectory tracking with the help of wireless sensor networks (WSNs). However, they have high complexity and cost to deploy multiple sensor nodes in WSNs. Different from these works, this paper proposes a new passive human trajectory tracking algorithm based on the channel state information (CSI) in indoor environment. In such an algorithm, we first use discrete wavelet transform to decrease noise in CSI, then use the time window of CSI time series to detect whether human moves or not, and finally quadratic discriminant analysis (QDA) is employed to determine the location of human. Experiment study is conducted to validate the algorithm and to illustrate performance findings.