一种ADCP鱼偏差抑制算法的评价

H. Freitag, P.E. Plimpton, M. Mcphaden
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引用次数: 9

摘要

与机械电流计(MCM)相比,水下系泊声学多普勒电流剖面仪(ADCP)的数据有时会偏向于较低的值。这种偏向已被证明是由于大型远洋鱼类被吸引到水面系泊处造成的。RD Instruments的adcp有一个可选的算法,试图限制由于fish引起的速度偏差。该算法对仪器的四束回波强度幅度进行比较,并剔除最高和最低回波强度幅度相差超过给定水平的样本。该算法的性能在东、西赤道太平洋的部署中进行了评估。在某些情况下,偏见被发现减少了,但在其他情况下仍然存在。剩余偏置的原因被证明是在所有四个声束中都存在鱼——这是算法没有考虑的条件。提出了一种校正ADCP速度数据中fish偏差的后处理方法。该方法涉及使用经验正交函数(EOFs)计算ADCP-MCM差异的偏差的垂直模式。将EOFs的垂直结构插值到ADCP的较高垂直分辨率,然后作为ADCP数据的校正。经此校正后,ADCP数据的质量显著提高。
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Evaluation of an ADCP fish-bias rejection algorithm
Downward-looking surface-moored Acoustic Doppler Current Profiler (ADCP) data is at times biased towards lower values when compared to mechanical current meters (MCM). This bias has been shown to be caused by the attraction of large pelagic fish to surface moorings. RD Instruments ADCPs have an optional algorithm which attempts to limit velocity bias due to fish. The algorithm compares echo intensity amplitude among the four beams of the instrument and rejects samples in which the highest and lowest echo intensity amplitude differ by more than a given level. The performance of the algorithm was evaluated at deployments in the eastern and western equatorial Pacific. Bias was found to be reduced in some cases, but remained in others. The cause of residual bias is shown to be the presence of fish in all four acoustic beams-a condition not considered by the algorithm. A post-processing method of correcting fish bias in ADCP velocity data is presented. The method involved computing vertical modes of the bias from ADCP-MCM differences using empirical orthogonal functions (EOFs). The vertical structure of the EOFs was interpolated to the higher vertical resolution of the ADCP and then applied as a correction to the ADCP data. The quality of ADCP data was significantly improved by this correction.<>
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