An indoor the real-time positioning technology based on Extended Kalman Filtering (EKF) algorithm is proposed to solve the problem that the forecasted position error is larger. Systems based on fingerprint positioning WiFi signal, and the Kalman filter is used to filter the forecasted location in order to improve the accuracy of WiFi fingerprinting positioning method, to achieve real-time tracking of the target. The simulation and experimental results illustrate that method improves the positioning precision, can better fulfil requirements of indoor positioning.