A robust indoor positioning system based on encoded magnetic field and low-cost IMU

This paper presents a positioning system based on encoded magnetic field and inertial measurement unit (IMU) to estimate the position and attitude of an object in indoor environment. The object used a tri-axial magnetometer to measure encoded magnetic field generated by multiple beacons using. Each beacon comprised coils which was designed to be identical and coaxially mounted on different stationary base. Each beacon was assigned a unique gold code using code division multiple access (CDMA) technology, and its location information was converted into binary equivalent as spreading code. The magnetic fields generated by each beacon were in accordance with code sequences at low frequency, which had good properties for none line of sight (NLOS) indoor environment, such as penetrating various obstacles, and robust to multipath. The magnitude and location of different magnetic beacons could be identified by correlation analysis, then the positon of object was able to be estimated. However, the magnetic positioning method had a disadvantage of low update rate. Thus, a low cost IMU was introduced to improve positioning update rate for kinematic application and the extended Kalman filter (EKF) was employed to integrate encoded magnetic field with IMU measurements. The variations of object position and orientation were estimated by IMU during magnetic updating period, and the system would not perform magnetic update when magnetic fields exceeded a predefined interference threshold. Since magnetic fields model error, eddy fields noise and metallic object interference may lead to divergence of magnetic positioning method, these error sources of magnetic positioning method were analyzed to minimize drifts of IMU. The proposed robust indoor positioning system based on encoded magnetic field and IMU was verified by both numerical simulation and indoor positioning experiment. The results showed that the proposed system enabled to estimate object position for real-time indoor positioning application.