A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN
At present, the interaction mechanism between the complex indoor environment and pseudolite signals has not been fundamentally resolved, and the stability, continuity, and accuracy of indoor positioning are still technical bottlenecks. In view of the shortcomings of the existing indoor fingerprint p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/14/8/235 |
| _version_ | 1797410164898267136 |
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| author | Yaning Li Hongsheng Li Baoguo Yu Jun Li |
| author_facet | Yaning Li Hongsheng Li Baoguo Yu Jun Li |
| author_sort | Yaning Li |
| collection | DOAJ |
| description | At present, the interaction mechanism between the complex indoor environment and pseudolite signals has not been fundamentally resolved, and the stability, continuity, and accuracy of indoor positioning are still technical bottlenecks. In view of the shortcomings of the existing indoor fingerprint positioning methods, this paper proposes a hybrid CSI fingerprint method for indoor pseudolite positioning based on Ray Tracing and artificial neural network (RT-ANN), which combines the advantages of actual acquisition, deterministic simulation, and artificial neural network, and adds the simulation CSI feature parameters generated by modeling and simulation to the input of the neural network, extending the sample features of the neural network input dataset. Taking an airport environment as an example, it is proved that the hybrid method can improve the positioning accuracy in the area where the fingerprints have been collected, the positioning error is reduced by 54.7% compared with the traditional fingerprint positioning method. It is also proved that preliminary positioning can be completed in the area without fingerprint collection. |
| first_indexed | 2024-03-09T04:24:58Z |
| format | Article |
| id | doaj.art-8c9c574e332d4ec2b62ba340e660dd90 |
| institution | Directory Open Access Journal |
| issn | 1999-5903 |
| language | English |
| last_indexed | 2024-03-09T04:24:58Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Internet |
| spelling | doaj.art-8c9c574e332d4ec2b62ba340e660dd902023-12-03T13:41:28ZengMDPI AGFuture Internet1999-59032022-07-0114823510.3390/fi14080235A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANNYaning Li0Hongsheng Li1Baoguo Yu2Jun Li3School of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaState Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang 050081, ChinaState Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang 050081, ChinaAt present, the interaction mechanism between the complex indoor environment and pseudolite signals has not been fundamentally resolved, and the stability, continuity, and accuracy of indoor positioning are still technical bottlenecks. In view of the shortcomings of the existing indoor fingerprint positioning methods, this paper proposes a hybrid CSI fingerprint method for indoor pseudolite positioning based on Ray Tracing and artificial neural network (RT-ANN), which combines the advantages of actual acquisition, deterministic simulation, and artificial neural network, and adds the simulation CSI feature parameters generated by modeling and simulation to the input of the neural network, extending the sample features of the neural network input dataset. Taking an airport environment as an example, it is proved that the hybrid method can improve the positioning accuracy in the area where the fingerprints have been collected, the positioning error is reduced by 54.7% compared with the traditional fingerprint positioning method. It is also proved that preliminary positioning can be completed in the area without fingerprint collection.https://www.mdpi.com/1999-5903/14/8/235CSI fingerprintANNpseudoliteray tracingindoor positioning |
| spellingShingle | Yaning Li Hongsheng Li Baoguo Yu Jun Li A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN Future Internet CSI fingerprint ANN pseudolite ray tracing indoor positioning |
| title | A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN |
| title_full | A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN |
| title_fullStr | A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN |
| title_full_unstemmed | A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN |
| title_short | A CSI Fingerprint Method for Indoor Pseudolite Positioning Based on RT-ANN |
| title_sort | csi fingerprint method for indoor pseudolite positioning based on rt ann |
| topic | CSI fingerprint ANN pseudolite ray tracing indoor positioning |
| url | https://www.mdpi.com/1999-5903/14/8/235 |
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