论文标题
高频雷达海洋电流映射以自回归建模快速规模
High-Frequency Radar Ocean Current Mapping at Rapid Scale with Autoregressive Modeling
论文作者
论文摘要
我们使用自回旋（AR）方法与最大熵方法（MEM）相结合来估算沿海高频雷达（HFR）复合电压时间序列的径向表面电流。使用合成HFR数据研究了该组合的AR-MEM模型的性能，并将其与经典多普勒频谱方法进行了比较。结果表明，AR-MEM极大地提高了表面电流估计在短整合时间的质量和成功率。为了确认这些数值结果，使用Toulon的16.3 MHz HFR获得的实验数据集进行了相同的分析。发现即使在非常短的集成时间（约1分钟）的情况下，AR-MEM技术也能够提供高质量和高覆盖的表面电流地图，在这种情况下，经典光谱方法只能在稀疏覆盖范围内完成质量测试。该技术的进一步有用的应用在高速颞分辨率的表面电流跟踪中。在分钟的时间尺度上的表面电流的快速变化已揭幕，并显示出与湍流光谱的$ f^{ - 5/3} $衰减一致的。
We use an Autoregressive (AR) approach combined with a Maximum Entropy Method (MEM) to estimate radial surface currents from coastal 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 16.3 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 minute) 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 a $f^{-5/3}$ decay of turbulent spectra.
