Multiple sensors integration for pedestrian indoor navigation

This paper discusses the fusion schemes of multiple sensors including accelerometer, gyro, magnetometer and pressure sensor for improved indoor positioning accuracy. The main focus is to make fully use of complementary features in sensors (such as gyro and magnetometer) and navigation structure (such as PDR and strapdown INS). A centralized Kalman filter is designed and implemented for this integration. Tests are conducted at indoor without using external wireless signal aiding. Positioning performance is evaluated among different integration strategies by different sensors and different complementary features.

[1]  O. Mezentsev,et al.  Sensor aiding of HSGPS pedestrian navigation , 2005 .

[2]  D. Gebre-Egziabher,et al.  A low-cost GPS/inertial attitude heading reference system (AHRS) for general aviation applications , 1998, IEEE 1998 Position Location and Navigation Symposium (Cat. No.98CH36153).

[3]  Jared B. Bancroft,et al.  Multiple Inertial Measurement Unit Integration for Pedestrian Navigation , 2010 .

[4]  P. Savage.  STRAPDOWN INERTIAL NAVIGATION INTEGRATION ALGORITHM DESIGN. PART 2: VELOCITY AND POSITION ALGORITHMS , 1998 .

[5]  Muhammad Haris Afzal,et al.  Use of Earth's Magnetic Field for Pedestrian Navigation , 2011 .

[6]  M. E. Cannon,et al.  Integrated GPS/INS System for Pedestrian Navigation in a Signal Degraded Environment , 2006 .

[7]  Leor Banin,et al.  Enhanced WiFi ToF indoor positioning system with MEMS-based INS and pedometric information , 2014, 2014 IEEE/ION Position, Location and Navigation Symposium - PLANS 2014.

[8]  Alessio De Angelis,et al.  A constraint approach for UWB and PDR fusion , 2012, 2012 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[9]  G. Lachapelle,et al.  Use of magnetic quasi static field (QSF) updates for pedestrian navigation , 2012, Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium.

[10]  P. Savage.  Strapdown Inertial Navigation Integration Algorithm Design Part 1: Attitude Algorithms , 1998 .

[11]  Valérie Renaudin,et al.  Use of Earth’s Magnetic Field for Mitigating Gyroscope Errors Regardless of Magnetic Perturbation , 2011, Sensors.