Abstract
Underground, indoor, and harsh environments, which are complex, mutable, and hard to model, prevent high accuracy positioning and navigation. In this paper, a novel positioning system suitable to such environments is proposed. This system is based on a magnetic feature vector integrated with a miniature inertial measurement unit (MIMU). Compared with traditional magnetic-based positioning systems (MBPS), the proposed system exhibits better robustness, and applicability, which is proved by experimental results. Its non-accumulated error characteristics and outstanding penetrability enable the system to provide long-time accurate position and attitude service in underground, indoor, and harsh environments. The experiments indicate that the expected precision of the system can reach 0.055 and 0.062 m and an angle error of 2.1° and 2.8° in line of sight (LOS) and non-line of sight (NLOS) environments, respectively, in the static experiment and 0.051 m in the moving target tracking experiment.
Highlights
GPS is known as the most popular system for navigation and positioning
The magnetic-based positioning method has attracted significant interest for indoor location and navigation [6]–[17] because it is less sensitive to propagation-dependent disturbances, penetration, and multipath effects compared to radio frequency (RF)-based methods
In this paper, an advanced magnetic-based positioning systems (MBPS) integrated with miniature inertial measurement unit (MIMU) was designed to solve the tracking moving target problem considering the time delay case
Summary
GPS is known as the most popular system for navigation and positioning. its use is impossible in some overbuild or blocked environments, such as indoor environments due to multipath effects, location, and navigation in indoor areas are hard to achieve. The magnetic-based positioning method has attracted significant interest for indoor location and navigation [6]–[17] because it is less sensitive to propagation-dependent disturbances, penetration, and multipath effects compared to radio frequency (RF)-based methods. A method, which uses a magnetic feature vector with a low frequency magnetic field capable of providing position, and attitude solution, is proposed. This method exhibits better robustness and applicability on harsh environments, which are complex, mutable, and hard to model, than traditional methods. Considering a low driving frequency and Shannon’s sampling theorem, the time delay from different MBs may contribute to extra positioning errors in real time navigation of moving targets.
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