Improvement in the Post-Processing of Wave Buoy Data Driven by the Needs of a National Coast and Sea Monitoring Agency

Abstract

Technological development in terms of the power requirement for data acquisition and processing opens new perspectives in the field of environmental monitoring. Near real-time data flow about the sea condition and a possible direct interface with applications and services devoted to marine weather networks would have a significant impact on several aspects, such as, for example, safety and efficiency. In this scenario, the needs of buoy networks have been analyzed, and the estimation of directional wave spectra from buoys’ data has been deeply investigated. Two methods have been implemented, namely the truncated Fourier series and the weighted truncated Fourier series, and they have been tested by both simulated and real experimental data, representative of typical Mediterranean Sea conditions. From simulation, the second method proved to be more efficient. From the application to real case studies, it emerged that it works effectively in real conditions, as confirmed by parallel meteorological observations. The estimation of the main propagation direction was possible with a small uncertainty of a few degrees, yet the method exhibits a limited directional resolution, which suggests the need for undertaking further studies, briefly addressed in the conclusions.

Advancements in Buoy Wave Data Processing through the Application of the Sage–Husa Adaptive Kalman Filtering Algorithm

“…This paper employs the improved windowed average periodogram method (Welch’s method [ 7 ]) to calculate the wave energy spectrum. The periodogram method calculates the wave spectrum data by performing a Fast Fourier Transform (FFT) on the wave surface displacement, considering the symmetry of the double-side spectrum, and then smoothing it.…”

“…Similarly, low-pass filtering has its limitations. In 2023, scholar Giovanni Battista Rossi [ 7 ] from Italy utilized a bandpass filter to process the signals measured by the Alghero buoy. Although setting appropriate upper and lower cutoff frequencies effectively filtered out zero-offset errors and low-frequency random noise, the fixed cutoff frequency revealed its significant shortcoming when sea conditions changed and the distribution of noise frequencies altered, namely its inability to adapt to noise frequencies under varying sea conditions.…”

Analysis and Prospects of an Antarctic Krill Detection Experiment Using Drifting Sonar Buoy

“…At the same time, sonar technology has been increasingly refined and integrated with emerging technologies like artificial intelligence, allowing it to better serve current production and research work. Buoys, as monitoring and navigational tools at sea, offer the advantages of low cost and flexible deployment [21,22], and they are currently widely used in fields such as marine research [23][24][25][26], navigational safety [27][28][29], meteorological monitoring [30][31][32][33], and fishery [34][35][36].…”