دورية أكاديمية
Magnetic Localization Method for Vehicles Based on Transformer.
| العنوان: | Magnetic Localization Method for Vehicles Based on Transformer. |
|---|---|
| المؤلفون: | Lu, Yi, Wei, Dongyan, Yuan, Hong |
| المصدر: | Applied Sciences (2076-3417); Apr2024, Vol. 14 Issue 7, p3079, 20p |
| مصطلحات موضوعية: | TRANSFORMER models, GLOBAL Positioning System, FEATURE extraction, VEHICLE routing problem, MAGNETIC levitation vehicles, DATABASES, LOCALIZATION (Mathematics) |
| مستخلص: | Magnetic positioning is a promising technique for vehicles in Global Navigation Satellite System (GNSS)-denied scenarios. Traditional magnetic positioning methods resolve the position coordinates by calculating the similarity between the measured sequence and the sequence generated from the magnetic database with criteria such as the Mean Absolute Difference (MAD), PRODuct correlation (PROD), etc., which usually suffer from a high mismatch rate. To solve this problem, we propose a novel magnetic localization method for vehicles based on Transformer. In this paper, we cast the magnetic localization problem as a regression task, in which a neural network is trained by equidistant sequences to predict the current position. In addition, by adopting Transformer to perform magnetic localization of vehicles for the first time, magnetic features are extracted, and positional relationships are explored to guarantee positioning accuracy. The experimental results show that the proposed method can greatly improve the magnetic positioning accuracy, with an average improvement of approximately 2 m. [ABSTRACT FROM AUTHOR] |
| Copyright of Applied Sciences (2076-3417) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| قاعدة البيانات: | Complementary Index |
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