Sea Spectral Estimation Using ARMA Models
This paper deals with the spectral estimation of sea wave elevation time series by means of ARMA models. To start, the procedure to estimate the ARMA coefficients, based on the use of the Prony’s method applied to the auto-covariance series, is presented. Afterwards, an analysis on how the parameter...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/13/4280 |
| _version_ | 1797529158932234240 |
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| author | Marta Berardengo Giovanni Battista Rossi Francesco Crenna |
| author_facet | Marta Berardengo Giovanni Battista Rossi Francesco Crenna |
| author_sort | Marta Berardengo |
| collection | DOAJ |
| description | This paper deals with the spectral estimation of sea wave elevation time series by means of ARMA models. To start, the procedure to estimate the ARMA coefficients, based on the use of the Prony’s method applied to the auto-covariance series, is presented. Afterwards, an analysis on how the parameters involved in the ARMA reconstruction procedure—for example, the signal time length, the number of poles and data used—affect the spectral estimates is carried out, providing evidence on their effect on the accuracy of results. This allowed us to provide guidelines on how to set these parameters in order to make the ARMA model as accurate as possible. The paper focuses on mono-modal sea states. Nevertheless, examples also related to bi-modal sea states are discussed. |
| first_indexed | 2024-03-10T10:09:46Z |
| format | Article |
| id | doaj.art-73a252f4a3f24839a8a8dd66642c29f7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T10:09:46Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-73a252f4a3f24839a8a8dd66642c29f72023-11-22T01:18:43ZengMDPI AGSensors1424-82202021-06-012113428010.3390/s21134280Sea Spectral Estimation Using ARMA ModelsMarta Berardengo0Giovanni Battista Rossi1Francesco Crenna2Department of Mechanical, Energy, Management and Transportation Engineering, University of Genova, Via Opera Pia 15A, 16145 Genova, ItalyDepartment of Mechanical, Energy, Management and Transportation Engineering, University of Genova, Via Opera Pia 15A, 16145 Genova, ItalyDepartment of Mechanical, Energy, Management and Transportation Engineering, University of Genova, Via Opera Pia 15A, 16145 Genova, ItalyThis paper deals with the spectral estimation of sea wave elevation time series by means of ARMA models. To start, the procedure to estimate the ARMA coefficients, based on the use of the Prony’s method applied to the auto-covariance series, is presented. Afterwards, an analysis on how the parameters involved in the ARMA reconstruction procedure—for example, the signal time length, the number of poles and data used—affect the spectral estimates is carried out, providing evidence on their effect on the accuracy of results. This allowed us to provide guidelines on how to set these parameters in order to make the ARMA model as accurate as possible. The paper focuses on mono-modal sea states. Nevertheless, examples also related to bi-modal sea states are discussed.https://www.mdpi.com/1424-8220/21/13/4280sea waves monitoringARMA modelProny methodspectral estimation |
| spellingShingle | Marta Berardengo Giovanni Battista Rossi Francesco Crenna Sea Spectral Estimation Using ARMA Models Sensors sea waves monitoring ARMA model Prony method spectral estimation |
| title | Sea Spectral Estimation Using ARMA Models |
| title_full | Sea Spectral Estimation Using ARMA Models |
| title_fullStr | Sea Spectral Estimation Using ARMA Models |
| title_full_unstemmed | Sea Spectral Estimation Using ARMA Models |
| title_short | Sea Spectral Estimation Using ARMA Models |
| title_sort | sea spectral estimation using arma models |
| topic | sea waves monitoring ARMA model Prony method spectral estimation |
| url | https://www.mdpi.com/1424-8220/21/13/4280 |
| work_keys_str_mv | AT martaberardengo seaspectralestimationusingarmamodels AT giovannibattistarossi seaspectralestimationusingarmamodels AT francescocrenna seaspectralestimationusingarmamodels |