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2D Estimation of Velocity Relative to Water and Tidal Currents Based on Differential Pressure for Autonomous Underwater Vehicles

机译:基于自动水下车辆的差压,2D估计相对于水和潮流的速度

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Reliable navigation of autonomous underwater vehicles (AUVs) depends on the quality of their state estimation. Providing robust velocity estimation thus plays an important role. While water currents are main contributors to the navigational uncertainty of AUVs, they are also an important variable for oceanographic research. For both reasons, water current estimation is desirable during AUV operations. State of the art velocity estimation relies on expensive acoustic sensors with considerable energy requirements and a large form factor such as Doppler Velocity Logs (DVL) and Acoustic Doppler Current Profilers (ADCP), while water currents are either estimated with the same sensors, or with algorithms that require accurate position feedback. In this letter, we introduce a low-cost, lightweight and energy efficient sensor (DPSSv2) to estimate fluid relative velocity in 2D based on differential pressure. The sensor is validated in field trials on-board an AUV in the presence of tidal currents. We further show that, while moving against the currents, our device is capable of estimating tidal currents in situ with comparable accuracy to a DVL, given a source for absolute vehicle velocity. Additionally, we establish the limitations of the current design of DPSSv2 while moving with the currents.
机译:自主水下车辆(AUV)的可靠导航取决于其国家估计的质量。因此,提供强大的速度估计起到重要作用。虽然水流是AUV的导航不确定性的主要贡献者,但它们也是海洋学研究的重要变量。出于两个原因,在AUV操作期间期望水流估计。最先进的速度估计依赖于具有相当大的能量要求的昂贵的声学传感器和大型形状因素,例如多普勒速度日志(DVL)和声学多普勒电流分析器(ADCP),而水电流估计使用相同的传感器或需要准确的位置反馈的算法。在这封信中,我们引入了低成本,轻质和节能的传感器(DPSSv2),以基于差压估计2D的流体相对速度。在潮流存在下,传感器在现场试验中验证了AUV的现场试验。我们进一步表明,在抵抗电流的同时,我们的设备能够以具有绝对车辆速度的来源的源极其以与DVL的相当精度估计潮汐电流。此外,我们在用电流移动时建立了DPSSv2当前设计的局限性。

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