Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal
Accurate evaporation duct prediction is one of the critical technologies for realizing the over-the-horizon impact of marine communication, ship radar, and other systems. Using GPS signals to invert evaporation ducts provides more benefits in terms of method realization and ease. In order to invert...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-12-01
|
| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/13/12/2091 |
| _version_ | 1797461476228726784 |
|---|---|
| author | Ming-Yu Cui Yu Zhang |
| author_facet | Ming-Yu Cui Yu Zhang |
| author_sort | Ming-Yu Cui |
| collection | DOAJ |
| description | Accurate evaporation duct prediction is one of the critical technologies for realizing the over-the-horizon impact of marine communication, ship radar, and other systems. Using GPS signals to invert evaporation ducts provides more benefits in terms of method realization and ease. In order to invert the evaporation duct from GPS-received power data, a deep learning technique based on Bayesian optimization is proposed to increase the prediction accuracy of evaporation ducts. The evaporation duct propagation mechanism of the GPS signal is explored. The GPS-received power is estimated using the two-parameter evaporation duct model, and a better neural network structure is built using Bayesian optimization. The study results show that the Bayesian optimization model has a smaller root mean square error (RMSE) than the human empirical model, which allows for rapid and accurate inversion of duct parameters even in noisy interference. |
| first_indexed | 2024-03-09T17:20:52Z |
| format | Article |
| id | doaj.art-2b2a50dc2a354f4699292caf172e0e37 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-09T17:20:52Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-2b2a50dc2a354f4699292caf172e0e372023-11-24T13:12:45ZengMDPI AGAtmosphere2073-44332022-12-011312209110.3390/atmos13122091Deep Learning Method for Evaporation Duct Inversion Based on GPS SignalMing-Yu Cui0Yu Zhang1College of Electronic and Electrical Engineering, Henan Normal University, Xinxiang 453600, ChinaCollege of Electronic and Electrical Engineering, Henan Normal University, Xinxiang 453600, ChinaAccurate evaporation duct prediction is one of the critical technologies for realizing the over-the-horizon impact of marine communication, ship radar, and other systems. Using GPS signals to invert evaporation ducts provides more benefits in terms of method realization and ease. In order to invert the evaporation duct from GPS-received power data, a deep learning technique based on Bayesian optimization is proposed to increase the prediction accuracy of evaporation ducts. The evaporation duct propagation mechanism of the GPS signal is explored. The GPS-received power is estimated using the two-parameter evaporation duct model, and a better neural network structure is built using Bayesian optimization. The study results show that the Bayesian optimization model has a smaller root mean square error (RMSE) than the human empirical model, which allows for rapid and accurate inversion of duct parameters even in noisy interference.https://www.mdpi.com/2073-4433/13/12/2091evaporation ductglobal positioning systemdeep learningBayesian optimization |
| spellingShingle | Ming-Yu Cui Yu Zhang Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal Atmosphere evaporation duct global positioning system deep learning Bayesian optimization |
| title | Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal |
| title_full | Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal |
| title_fullStr | Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal |
| title_full_unstemmed | Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal |
| title_short | Deep Learning Method for Evaporation Duct Inversion Based on GPS Signal |
| title_sort | deep learning method for evaporation duct inversion based on gps signal |
| topic | evaporation duct global positioning system deep learning Bayesian optimization |
| url | https://www.mdpi.com/2073-4433/13/12/2091 |
| work_keys_str_mv | AT mingyucui deeplearningmethodforevaporationductinversionbasedongpssignal AT yuzhang deeplearningmethodforevaporationductinversionbasedongpssignal |