Chrome Extension
WeChat Mini Program
Use on ChatGLM

High-Frequency Radar Ocean Current Mapping at Rapid Scale With Autoregressive Modeling

IEEE Journal of Oceanic Engineering(2021)

Cited 10|Views4
No score
Abstract
In this article, we use an autoregressive (AR) approach combined with a maximum entropy method (MEM) to estimate radial surface currents fromcoastal high-frequency radar (HFR) complex voltage time-series. The performances of this combined AR-MEM model are investigated with synthetic HFR data and compared with the classical Doppler spectrum approach. It is shown that AR-MEM drastically improves the quality and the rate of success of the surface current estimation for short integration time. To confirm these numerical results, the same analysis is conducted with an experimental data set acquired with a 16.15-MHz HFR in Toulon. It is found that the AR-MEM technique is able to provide high-quality and high-coverage maps of surface currents even with very short integration time (about 1 min) where the classical spectral approach can only fulfill the quality tests on a sparse coverage. Further useful application of the technique is found in the tracking of surface current at high-temporal resolution. Rapid variations of the surface current at the time scale of the minute are unveiled and shown consistent with an f(-5/3) decay of turbulent spectra.
More
Translated text
Key words
Autoregressive (AR) model,Bragg scattering,coastal radar signal processing,high-frequency radar (HFR),maximum entropy method (MEM),multistatic radar
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined