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<p>Autonomous vehicles (AVs) are commonly used in oceanic and more recently estuarine and riverine environments because they are small, versatile, efficient, moving platforms equipped with a suite of instruments for measuring environmental conditions. However, moving vessel observations, particularly those associated with Acoustic Doppler Current Profiler (ADCP) measurements, can be problematic owing to instrument noise, flow fluctuations, and spatial variability. A range of ADCPs manufactured by different companies were integrated onto an Unmanned Surface Vehicle (USV), an Unmanned Underwater Vehicle (UUV), and some additional stationary platforms, and were deployed in a number of natural riverine and estuarine environments to evaluate the quality of the velocity profile over the depth, minimum averaging time interval requirements and AV mission planning considerations. An appropriate averaging window, T*, was determined using the Kalman Algorithm with a Kalman gain equal to 1%. T* was found to be independent of depth, flow velocity, and environment. There was no correlation (R2=0.18) for T* between flow magnitude and direction. Results from all measurements had a similar T* of approximately 3 minutes. Based on this, an averaging window of 4 minutes is conservatively suggested to obtain a statistically confident measure of the mean velocity profile.
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<br>Subjects: Remote submersibles; Estuaries</div>
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Tuggle, Christopher K.</div>
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