Indoor Positioning Based on Pedestrian Dead Reckoning and Magnetic Field Matching for Smartphones.

Jian Kuang,Peng Zhang,Xiaoji Niu,Xingeng Chen

doi:10.3390/s18124142

Abstract

This paper presents an ambient magnetic field map-based matching (MM) positioning algorithm for smartphones in an indoor environment. To improve the low distinguishability of a magnetic field fingerprint at a single point, a magnetic field sequence (MFS) combined with the measured trajectory contour coming from pedestrian dead-reckoning (PDR) is used for MM. Based on the fast approximation of magnetic field gradient, a Gauss-Newton iterative (GNI) method is used to find a rigid transformation that optimally aligns the measured MFS with a reference MFS coming from the magnetic field map. Then, the position of the reference MFS is used to control the position drift error of the inertial navigation system (INS) based PDR by an extended Kalman filter (EKF) and to further improve the accuracy of the trajectory contour. Finally, we conduct several experiments to evaluate the navigation performance of the proposed MM algorithm. The test results show that the position estimation error of the MM algorithm is 0.64 m (RMS) in an office building environment, 1.87 m (RMS) in a typical lobby environment, and 2.34 m (RMS) in a shopping mall environment.

Highlights

Global navigation satellite systems (GNSSs) can provide accurate location service for pedestrians in open-sky outdoor scenarios, but GNSSs are hindered by signal attenuation and blockage in certain environments
Inspired by the traditional magnetic field matching algorithms, we use magnetic field sequences combined with the trajectory contour to improve the positioning performance of a smartphone
The second trajectory is in building B, which is a typical lobby in an indoor environment

Summary

Introduction

Global navigation satellite systems (GNSSs) can provide accurate location service for pedestrians in open-sky outdoor scenarios, but GNSSs are hindered by signal attenuation and blockage in certain environments (e.g., indoor environments). To provide ubiquitous location service, a number of technologies have been developed for indoor positioning, such as pseudo-satellites [1], ZigBee [2], ultra-wideband (UWB) [3], radio frequency identification (RFID) [4], infrared [5], ultrasonic [5], iBeacon [6]. These methods are all capable of providing a high-precision positioning service for pedestrians over a long time scale in an indoor environment. It is still expensive to maintain a robust Wi-Fi-based localization system due to the unexpected changes in the position and working status of Wi-Fi APs [7,8]

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Discussion

Conclusion