Swarm Optimization-Based Magnetometer Calibration for Personal Handheld Devices

Sensors

Abdelrahman Ali¹  Siddharth Siddharth¹  Zainab Syed² 

[1] Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; E-Mails:;Alastair Ross Technology Centre, Trusted Positioning Inc. (TPI), Calgary, AB T2L 2K7, Canada; E-Mail:

关键词: artificial intelligence;    systems;    measurement;    navigation;    algorithms;    sensor;   

DOI  :  10.3390/s120912455

来源: mdpi

【 摘 要 】

Inertial Navigation Systems (INS) consist of accelerometers, gyroscopes and a processor that generates position and orientation solutions by integrating the specific forces and rotation rates. In addition to the accelerometers and gyroscopes, magnetometers can be used to derive the user heading based on Earth's magnetic field. Unfortunately, the measurements of the magnetic field obtained with low cost sensors are usually corrupted by several errors, including manufacturing defects and external electro-magnetic fields. Consequently, proper calibration of the magnetometer is required to achieve high accuracy heading measurements. In this paper, a Particle Swarm Optimization (PSO)-based calibration algorithm is presented to estimate the values of the bias and scale factor of low cost magnetometers. The main advantage of this technique is the use of the artificial intelligence which does not need any error modeling or awareness of the nonlinearity. Furthermore, the proposed algorithm can help in the development of Pedestrian Navigation Devices (PNDs) when combined with inertial sensors and GPS/Wi-Fi for indoor navigation and Location Based Services (LBS) applications.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.