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首页> 外文期刊>Oceanic Engineering, IEEE Journal of >An Efficient, Time-of-Flight-Based Underwater Acoustic Ranging System for Small Robotic Fish
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An Efficient, Time-of-Flight-Based Underwater Acoustic Ranging System for Small Robotic Fish

机译:小型机鱼的高效,基于飞行时间的水下声测距系统

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摘要

Small (decimeter-scale) robotic fish are promising mobile sensor platforms for aquatic environments. Fine-grained localization for dense networks of such robotic fish presents a challenge because of noisy underwater environment, required submeter accuracy, and constraints on onboard processing power and hardware complexity. In this paper, we present an efficient time-of-flight-based acoustic ranging system for localization of robotic fish with limited onboard resources. The system involves simple hardware: a single pair of monotone buzzer and microphone. The distance between two nodes is determined by the time it takes for an acoustic signal generated by the buzzer on the first node to reach the microphone on the second node. The arrival of the signal is detected with the sliding discrete Fourier transform (SDFT) algorithm, where the rise dynamics of the signal is modeled and used for compensation of detection latency. The algorithm is implemented onboard a small biomimetic robotic fish, and experiments in an indoor pool have shown that the compensated SDFT algorithm results in an underwater ranging error of 1.9 wavelengths (1 m), and is thus promising for localization of dense aquatic networks.
机译:小型(厘米级)机器人鱼是有前途的水生环境移动传感器平台。由于嘈杂的水下环境,所需的亚米级精度以及对机载处理能力和硬件复杂性的限制,此类机器人鱼的密集网络的细粒度定位提出了挑战。在本文中,我们提出了一种有效的基于飞行时间的声波测距系统,用于在机载资源有限的情况下对机器鱼进行定位。该系统涉及简单的硬件:一对单调蜂鸣器和麦克风。两个节点之间的距离由第一节点上的蜂鸣器生成的声音信号到达第二节点上的麦克风所花费的时间确定。使用滑动离散傅立叶变换(SDFT)算法检测信号的到达,在该算法中,对信号的上升动力学建模并用于补偿检测延迟。该算法是在小型仿生机器人鱼上实现的,室内游泳池的实验表明,补偿后的SDFT算法会导致1.9个波长(1 m)的水下测距误差,因此有望用于密集水生网络的定位。

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