从底部安装的压力和电流传感器的定向波时间序列的相干性检查

J. P. McKinney, G. Howell
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摘要

本文研究了用于海岸定向波测量的不同类型的底部安装仪器的运动变量之间的一致性。PPP、PEMCM和PADV在多个地点和波浪条件下的长期现场数据进行了波的方向和相干性分析。从传感器阵列分析的定向波测量假设波浪运动学的时间序列在统计上是均匀的。传感器时间序列只应在幅度和相位上不同。对于现实世界的现场测量,传感器数据包含噪声成分和系统误差和偏差。传感器对之间的相干性是一种常用的量化噪声和误差的方法。我们的结果表明,在短基线压力阵列中,单个压力时间序列之间具有非常高的一致性。从压力阵计算得到的坡度分量用于定向分析。我们发现斜率相干性小于标量压力,但通常较高。流速仪测量的水平速度U和V分量之间的相干性应该很高,因为它们是电流矢量的笛卡尔分量。我们的数据表明,对于普通的E-M电流表来说,这通常是正确的。对于声学多普勒测速仪,相干性明显降低。相干性是比较不同传感器系统方向估计精度的潜在有用度量。它也经常被用作自动化数据分析的质量控制测试。非声学系统在正确操作时通常表现出高相干性。对于声学系统,出现的问题是,对于可接受的数据,相干性必须有多好。我们提出了探索性分析,研究了相干性和定向估计质量之间的关系。
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An examination of coherence of directional wave time series from bottom-mounted pressure and current sensors
This paper examines the coherence between kinematic variables from different types of bottom mounted instruments used for coastal directional wave measurements. Long term field data from PPP, PEMCM and PADV for several locations and wave conditions are analyzed for wave direction and coherence. Directional wave measurements analyzed from arrays of sensors assume that the time series of wave kinematics are statistically homogenous. Sensor time series should differ only in amplitude and phase. For real-world field measurements sensor data contains noise components and systematic errors and biases. Coherence between sensor pairs is a common method of quantifying the noise and error. Our results show very high coherence between individual pressure time series in short base-line pressure arrays. Slope components computed from the pressure array are used for directional analysis. We find slope coherence less than the scalar pressures but generally high. Coherence between U and V components of horizontal velocity measured by current meters should be very high because they are Cartesian components of the current vector. Our data show this is generally true for common E-M current meters. For acoustic Doppler (PADV) velocity meters the coherence was significantly lower. Coherence is potentially useful as a metric for comparing different sensor systems accuracy for directional estimates. It also is frequently used as a quality control test for automated data analysis. Non-acoustic systems generally exhibit high coherence when operating correctly. For acoustic systems, the question arises as how good must coherence be for acceptable data. We present exploratory analyses that examine then relationship between coherence and the quality of directional estimates.
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