Abstract
In this article, we propose a new geomagnetic localization scheme, named ILoA, to address error accumulation and global localization. Global localization is a fundamental problem that determines the initial pose under global uncertainty. Moreover, error accumulation using inertial navigation systems (INS) impacts robustness and drift error, making it challenging to achieve reliable estimation. The magnetic field in indoor space generates a unique signature/anomaly, which can be used as a local feature. Earth’s magnetic field can be easily influenced by ferromagnetic material from the indoor environment due to its weak intensity. The magnetic field vector measured by a magnetometer depends on the orientation of the sensor, which we term a direction variant. We devise a novel approach to identify location and heading through the direction-variant augmented vector. Since a magnetic field vector under varying poses can produce many different vectors, the geomagnetic map is trained with the transformation. We present experiments in two testbeds, covering open space, showing that the proposed method using the magnetic field vector is efficient for global localization and accuracy compared with a state-of-the-art approach.
Highlights
Indoor positioning and tracking problems are receiving increasing attention in the Internet of Things (IoT) era
The problem is that wireless local area network (WLAN)-based techniques are insufficient to accurately localize because received signal strength (RSS) is prone to be affected by environmental noise such as multipath fading
The effectiveness of the augmented geomagnetic vector was demonstrated in a variety of path scenarios by solving the global localization problem
Summary
Indoor positioning and tracking problems are receiving increasing attention in the Internet of Things (IoT) era. RF fingerprinting localization technique, such as a wireless local area network (WLAN) fingerprinting [1]–[3], is one of most well-known methods that use the received signal strength (RSS). This system exploits existing wireless access points (APs) installed in indoor spaces, and it simplifies the deployment process with no additional cost. A system with a single sensor suffers from ambiguity of measurement. The sensor fusion technique addresses single-sensor ambiguity by combining the measurements from multiple sensors. The pedestrian dead reckoning (PDR) technique with off-the-shelf inertial measurement units (IMUs) in a smartphone is often combined with multiple
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