An Enhanced Indoor Ranging Method Using CSI Measurements with Extended Kalman Filter

摘要

For indoor positioning, the navigation satellite signal is difficult to cover, and the wireless base station signal multipath and attenuation characteristics are complicated, resulting in low positioning accuracy and large jitter. Wi-Fi signal is an important positioning source and has long been concerned by researchers. With the development of Wi-Fi technology, the IEEE 802.11n series communication protocol and the subsequent wireless LAN protocols use multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) and other technologies. Channel characteristics between Wi-Fi transceivers can be estimated at the physical layer and stored in the form of channel state information (CSI). WI-FI using CSI technology have emerged as a new paradigm of indoor positioning service (IPS). In this paper, we proposes a CSI based indoor ranging method using an extended Kalman filter(EKF) that recursively processes input data including noise. To make EKF applicable, we develop a measurement model based on CSI estimation, which enables accurate indoor ranging and measurement noise statistics estimation. This paper also provides experimental comparisons of our proposed EKF method with existing indoor ranging methods. Experimental results show that the proposed EKF based CSI estimation approach achieves significant ranging accuracy improvement over using raw CSI ranging method, while it incurs much less computational complexity.