Extended Kalman filter for a low cost TDoA/IMU pedestrian localization system

Pedestrian localization systems require the knowledge of a user´s position for manifold applications in indoor and outdoor environments. For this purpose several methods can be used, such as a Global Navigation Satellite System (GNSS) or an Inertial Navigation Systems (INS). Since GNSS are not available in indoor environments or street canyons a Time Difference of Arrival (TDoA) system and a low cost Inertial Measurement Unit (IMU), which consists of an accelerometer and a gyroscope, is used to estimate the position of a pedestrian. The localization device is mountable to different positions of the body, like the hip or the pocket of a shirt. The measurements of the IMU are prefiltered to get steps, the step length and fast changings in the user´s orientation. To fuse the different measurement types an Extended Kalman Filter (EKF) is applied. To evaluate the algorithm experimental results are presented.