Research and Scheme Design of Space Positioning System Based on Magnetic Field

Autonomous underwater vehicles (AUV) are seen as an emerging technology for maritime exploration but are still restricted by the availability of short range, accurate positioning methods necessary, e.g., when docking remote assets. Typical techniques used for high-accuracy positioning in indoor use case scenarios, such as systems using ultra-wide band radio signals (UWB), cannot be applied for underwater positioning because of the quick absorption of the positioning medium caused by the water. Acoustic and optic solutions for underwater positioning also face known problems, such as the multi-path effects, high propagation delay (acoustics), and environmental dependency. This paper presents an oscillating magnetic field-based indoor and underwater positioning system. Unlike those radio wave-based positioning modalities, the magnetic approach generates a bubble-formed magnetic field that will not be deformed by the environmental variation because of the very similar permeability of water and air. The proposed system achieves an underwater positioning mean accuracy of 13.3 cm in 2D and 19.0 cm in 3D with the multi-lateration positioning method and concludes the potential of the magnetic field-based positioning technique for underwater applications. A similar accuracy was also achieved for various indoor environments that were used to test the influence of cluttered environment and of cross environment. The low cost and power consumption system is scalable for extensive coverage area and could plug-and-play without pre-calibration.

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Mapping of Magnetic Field of SPIDER by a Three-Axis Automatic Positioning System

IEEE Transactions on Plasma Science ◽

10.1109/tps.2019.2955063 ◽

2020 ◽

Vol 48 (6) ◽

pp. 1566-1571

Author(s):

Daniele Aprile ◽

Piero Agostinetti ◽

Sylvestre Denizeau ◽

Giuseppe Chitarin

Keyword(s):

Magnetic Field ◽

Positioning System ◽

Automatic Positioning

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Magnetic field indoor positioning system based on automatic spatial-segmentation strategy

2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN) ◽

10.1109/ipin.2017.8115866 ◽

2017 ◽

Cited By ~ 3

Author(s):

Yichen Du ◽

Tughrul Arslan

Keyword(s):

Magnetic Field ◽

Indoor Positioning ◽

Positioning System ◽

Spatial Segmentation ◽

Segmentation Strategy ◽

Indoor Positioning System

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THE DESIGN AND IMPLEMENTATION OF INDOOR LOCALIZATION SYSTEM USING MAGNETIC FIELD BASED ON SMARTPHONE

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-2-w7-379-2017 ◽

2017 ◽

Vol XLII-2/W7 ◽

pp. 379-383

Author(s):

J. Liu ◽

C. Jiang ◽

Z. Shi

Keyword(s):

Magnetic Field ◽

Indoor Localization ◽

Indoor Positioning ◽

Positioning System ◽

Localization Algorithm ◽

External Device ◽

Localization System ◽

Filtering Algorithm ◽

Coordinate Conversion ◽

Indoor Positioning System

Sufficient signal nodes are mostly required to implement indoor localization in mainstream research. Magnetic field take advantage of high precision, stable and reliability, and the reception of magnetic field signals is reliable and uncomplicated, it could be realized by geomagnetic sensor on smartphone, without external device. After the study of indoor positioning technologies, choose the geomagnetic field data as fingerprints to design an indoor localization system based on smartphone. A localization algorithm that appropriate geomagnetic matching is designed, and present filtering algorithm and algorithm for coordinate conversion. With the implement of plot geomagnetic fingerprints, the indoor positioning of smartphone without depending on external devices can be achieved. Finally, an indoor positioning system which is based on Android platform is successfully designed, through the experiments, proved the capability and effectiveness of indoor localization algorithm.

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Indoor Positioning Using Magnetic Fingerprint Map Captured by Magnetic Sensor Array

Sensors ◽

10.3390/s21175707 ◽

2021 ◽

Vol 21 (17) ◽

pp. 5707

Author(s):

Ching-Han Chen ◽

Pi-Wei Chen ◽

Pi-Jhong Chen ◽

Tzung-Hsin Liu

Keyword(s):

Magnetic Field ◽

Sensor Array ◽

Probabilistic Neural Network ◽

Indoor Positioning ◽

Magnetic Sensor ◽

Magnetic Sensors ◽

Positioning System ◽

Positioning Accuracy ◽

Positioning Method ◽

The Magnetic Field

By collecting the magnetic field information of each spatial point, we can build a magnetic field fingerprint map. When the user is positioning, the magnetic field measured by the sensor is matched with the magnetic field fingerprint map to identify the user’s location. However, since the magnetic field is easily affected by external magnetic fields and magnetic storms, which can lead to “local temporal-spatial variation”, it is difficult to construct a stable and accurate magnetic field fingerprint map for indoor positioning. This research proposes a new magnetic indoor positioning method, which combines a magnetic sensor array composed of three magnetic sensors and a recurrent probabilistic neural network (RPNN) to realize a high-precision indoor positioning system. The magnetic sensor array can detect subtle magnetic anomalies and spatial variations to improve the stability and accuracy of magnetic field fingerprint maps, and the RPNN model is built for recognizing magnetic field fingerprint. We implement an embedded magnetic sensor array positioning system, which is evaluated in an experimental environment. Our method can reduce the noise caused by the spatial-temporal variation of the magnetic field, thus greatly improving the indoor positioning accuracy, reaching an average positioning accuracy of 0.78 m.

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