Towards Accurate Parameter Estimation of WiFi Signal Using Sparse Recovery

Abstract

Parameter estimation plays a significant role in many intelligent applications such as indoor passive localization and tracking based on WiFi signals. In this paper, we propose a super-resolution algorithm based on sparse recovery to estimate the parameters of WiFi signal. Specifically, we first jointly esti-mate the Angle of Arrival (AoA) and Time of Flight (ToF) using sparse recovery. Then, we use time alignment and singular value decomposition with multiple channel state information packets to obtain more accurate parameters. We conduct experiments in an actual indoor environment, and the experimental results show that this method can obtain accurate parameters.