Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation
The Global Positioning System (GPS) has revolutionized navigation in modern society. However, the susceptibility of GPS signals to interference and obstruction poses significant navigational challenges. This paper introduces a GPS-denied method based on scene image coordinates instead of real-time G...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/12/1/39 |
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| author | Zi-Ming Wang Chun-Liang Lin Chian-Yu Lu Po-Chun Wu Yang-Yi Chen |
| author_facet | Zi-Ming Wang Chun-Liang Lin Chian-Yu Lu Po-Chun Wu Yang-Yi Chen |
| author_sort | Zi-Ming Wang |
| collection | DOAJ |
| description | The Global Positioning System (GPS) has revolutionized navigation in modern society. However, the susceptibility of GPS signals to interference and obstruction poses significant navigational challenges. This paper introduces a GPS-denied method based on scene image coordinates instead of real-time GPS signals. Our approach harnesses advanced image feature-recognition techniques, employing an enhanced scale-invariant feature transform algorithm and a neural network model. The recognition of prominent scene features is prioritized, thus improving recognition speed and precision. The GPS coordinates are extracted from the best-matching image by juxtaposing recognized features from the pre-established image database. A Kalman filter facilitates the fusion of these coordinates with inertial measurement unit data. Furthermore, ground scene recognition cooperates with its aerial counterpart to overcome specific challenges. This innovative idea enables heterogeneous collaboration by employing coordinate conversion formulas, effectively substituting traditional GPS signals. The proposed scheme may include military missions, rescues, and commercial services as potential applications. |
| format | Article |
| id | doaj-art-d140b6e613324a5ead9d01802ff94555 |
| institution | Kabale University |
| issn | 2226-4310 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj-art-d140b6e613324a5ead9d01802ff945552025-01-24T13:15:34ZengMDPI AGAerospace2226-43102025-01-011213910.3390/aerospace12010039Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial NavigationZi-Ming Wang0Chun-Liang Lin1Chian-Yu Lu2Po-Chun Wu3Yang-Yi Chen4Department of Electrical Engineering, National Chung Hsing University, Taichung 402202, TaiwanDepartment of Electrical Engineering, National Chung Hsing University, Taichung 402202, TaiwanDepartment of Electrical Engineering, National Chung Hsing University, Taichung 402202, TaiwanDepartment of Electrical Engineering, National Chung Hsing University, Taichung 402202, TaiwanDepartment of Electrical Engineering, National Chung Hsing University, Taichung 402202, TaiwanThe Global Positioning System (GPS) has revolutionized navigation in modern society. However, the susceptibility of GPS signals to interference and obstruction poses significant navigational challenges. This paper introduces a GPS-denied method based on scene image coordinates instead of real-time GPS signals. Our approach harnesses advanced image feature-recognition techniques, employing an enhanced scale-invariant feature transform algorithm and a neural network model. The recognition of prominent scene features is prioritized, thus improving recognition speed and precision. The GPS coordinates are extracted from the best-matching image by juxtaposing recognized features from the pre-established image database. A Kalman filter facilitates the fusion of these coordinates with inertial measurement unit data. Furthermore, ground scene recognition cooperates with its aerial counterpart to overcome specific challenges. This innovative idea enables heterogeneous collaboration by employing coordinate conversion formulas, effectively substituting traditional GPS signals. The proposed scheme may include military missions, rescues, and commercial services as potential applications.https://www.mdpi.com/2226-4310/12/1/39GPS-denied navigationimage feature recognitionscale-invariant feature transform (SIFT)Kalman filter fusion |
| spellingShingle | Zi-Ming Wang Chun-Liang Lin Chian-Yu Lu Po-Chun Wu Yang-Yi Chen Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation Aerospace GPS-denied navigation image feature recognition scale-invariant feature transform (SIFT) Kalman filter fusion |
| title | Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation |
| title_full | Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation |
| title_fullStr | Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation |
| title_full_unstemmed | Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation |
| title_short | Dual-Vehicle Heterogeneous Collaborative Scheme with Image-Aided Inertial Navigation |
| title_sort | dual vehicle heterogeneous collaborative scheme with image aided inertial navigation |
| topic | GPS-denied navigation image feature recognition scale-invariant feature transform (SIFT) Kalman filter fusion |
| url | https://www.mdpi.com/2226-4310/12/1/39 |
| work_keys_str_mv | AT zimingwang dualvehicleheterogeneouscollaborativeschemewithimageaidedinertialnavigation AT chunlianglin dualvehicleheterogeneouscollaborativeschemewithimageaidedinertialnavigation AT chianyulu dualvehicleheterogeneouscollaborativeschemewithimageaidedinertialnavigation AT pochunwu dualvehicleheterogeneouscollaborativeschemewithimageaidedinertialnavigation AT yangyichen dualvehicleheterogeneouscollaborativeschemewithimageaidedinertialnavigation |