Abstract
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.
Highlights
Indoor Positioning Systems (IPS) for pedestrians, aiming at providing accurate indoor position information for tracking and navigation, are of significant interest for increasing number of Location Based Services (LBS)
We propose a hybrid indoor localization and navigation (HILN) system for pedestrians combining the advantages of both the Radio Frequency (RF) and Inertial Navigation Systems (INS) systems
Antonio et al [14] proposed a Pedestrian dead reckoning (PDR) system with ramp detection capable of providing drift-free localization in long-distance walks over one kilometer, but the approach relies on regular ramps located along the path, which significantly limits the practical deployment of the system as ramps are structural features of a building
Summary
Indoor Positioning Systems (IPS) for pedestrians, aiming at providing accurate indoor position information for tracking and navigation, are of significant interest for increasing number of Location Based Services (LBS). Trilateration, triangulation or fingerprinting is commonly used to obtain location information based on the signal characteristics such as received signal strength indicator (RSSI) [2], angle-of-arrival (AoA) and time-of-arrival (ToA) [4] These approaches suffer from indoor environment fluctuation and multi-path problems, while signal fingerprinting [3] requires a radio map to be established before deployment. By combining with traditional PDR, the exact position obtained can be used to calibrate the error caused by sensor drift in PDR, enabling PDR to offer long-term accurate positioning performance as long as SRP devices are available with reasonable density. The proposed system is capable of providing reliable long-term localization and tracking performance with satisfactory accuracy while operating on off-the-shelf devices In this case, real-time navigation is achieved on the tracked smartphone itself.
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