Department of Mechanical, Energy, Management and Transportation Engineering, University of Genova, Via Opera Pia 15A, 16145 Genova, Italy.
Sensors (Basel). 2021 Jun 23;21(13):4280. doi: 10.3390/s21134280.
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.
本文通过 ARMA 模型研究了海浪高程时间序列的谱估计。首先，介绍了基于普朗尼方法应用于自协方差序列来估计 ARMA 系数的过程。随后，分析了 ARMA 重构过程中涉及的参数（例如信号时间长度、极点数量和使用的数据）如何影响谱估计，为这些参数对结果准确性的影响提供了证据。这使我们能够提供有关如何设置这些参数的指南，以使 ARMA 模型尽可能准确。本文侧重于单峰海浪状态。然而，也讨论了与双峰海浪状态相关的示例。
