This paper proposes an approach for pedestrian tracking using dead reckoning enhanced with a mode detection using a standard smartphone. The mode represents a specific state of carrying device, and it is automatically detected while a person is walking. This paper presents a new approach, which extends and enhances previous methods by identifying in real-time three typical modes of carrying the device and using the identified mode to enhance tracking accuracy. The way of carrying the device in all modes is unconstrained to offer reliable person-independent tracking. Based on the identification of modes, a lightweight step-based tracking algorithm is developed with a novel step length estimation model. The tracking system is implemented on a commercial off-the-shelf smartphone equipped with a built-in inertial measurement unit with 3-D accelerometer and gyroscope. It achieves real-time tracking and localization performance with an average position accuracy of 98.91%.

Inertial Navigation System (INS) using kinematic sensors is able to provide accurate pedestrian tracking over a short distance. Information fusion of INS with wireless technology has been commonly employed to develop more robust and accurate tracking systems over longer distances. Ultra-Wideband (UWB) based system offers further improvement and achieves positioning error in order of centimetres. Existing INS and UWB integrated systems require at least three anchors at known locations for positioning in the covered area. The deployment cost of such systems is high since UWB devices are more expensive than other commonly used wireless nodes. The need to obtain the exact locations of all anchor nodes also contribute to additional cost in system deployment. In this paper, a low-cost INS and UWB integrated pedestrian tracking system is proposed using only one UWB anchor node at an unknown location, minimizing infrastructure cost and setup. The anchor location is estimated at the initial stage of tracking with the aid of INS tracking algorithm. Afterwards, the UWB ranging measurements are fused with INS data to provide robust and accurate tracking performance. The system is evaluated with pedestrian tracking experiments over long distances and achieves up to 85.75 % reduction in average positioning error when compared to an INS only solution.

Pedestrian dead reckoning is a common technique applied in indoor inertial navigation systems that is able to provide accurate tracking performance within short distances. Sensor drift is the main bottleneck in extending the system to long-distance and long-term tracking. In this paper, a hybrid system integrating traditional pedestrian dead reckoning based on the use of inertial measurement units, short-range radio frequency systems and particle filter map matching is proposed. The system is a drift-free pedestrian navigation system where position error and sensor drift is regularly corrected and is able to provide long-term accurate and reliable tracking. Moreover, the whole system is implemented on a commercial off-the-shelf smartphone and achieves real-time positioning and tracking performance with satisfactory accuracy.