Indoor Pedestrian Mobile Activity Recognition and Trajectory Tracking

As the basis of indoor location services, indoor localization technology has received more and more attention in recent years. Aiming at the problems of high cost, limited precision and insufficient efficiency in existing indoor positioning technologies, pedestrian dead reckoning (PDR), human acti-vity recognition (HAR) and landmarks are combined to obtain more accurate pedestrian indoor localization. PDR is used to estimate the user's location, and the cumulative error of PDR is reduced by landmarks, which are sensed by HAR. In addition, to solve the initial position determination problem, a hidden Markov model that considers the characteristics of the indoor environment is applied to match the continuous trajectory. The experimental results show that the proposed method has a good performance in activity recognition and positioning accuracy, and can track the user's trajectory efficiently.