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24490 Underwater Localization by combining Time-of-Flight and Direction-of-Arrival
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van Kleunen, W.A.P. and Blom, K.C.H. and Meratnia, N. and Kokkeler, A.B.J. and Havinga, P.J.M. and Smit, G.J.M. (2014) Underwater Localization by combining Time-of-Flight and Direction-of-Arrival. In: Proceedings of the Oceans 2014 MTS/IEEE Conference, 7-10 Apr 2014, Taipei, Taiwan. pp. 1-6. IEEE Computer Society. ISBN 978-1-4799-3645-8

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In this paper we present a combined ToF and DoA localization approach suitable for shallow underwater monitoring applications such as harbor monitoring. Our localization approach combines one-way ranging and DoA estimation to calculate both position and time-synchronization of the blind-node. We will show that using this localization approach, we are able to reduce the number of reference nodes required to perform localization. By combining ToF and DoA, our approach is also capable of tracking and positioning of sound sources under water.

We evaluate our approach through both simulation and underwater experiments in a ten meter deep dive-center (which has many similarities with our target application in terms of depth and reflection). Measurements taken at the dive-center show that this environment is highly reflective and resembles a shallow water harbor environment.

Positioning results using the measured ToA and DoA indicate that the DoA approach outperforms the ToF approach in our setup. Investigation of the DoA and ToF measurement error distributions, however, indicate the ToF-based localization approach has a higher precision. Shown is that both ToF and DoA and the combined approach achieve sub-meter positional accuracy in the test environment.

Using the error distributions derived from the measurement in the dive-center, we run simulations of the same setup. Results from the simulation indicate ToF is more accurate than DoA positioning. Also in simulation all approaches achieve sub-meter accuracy.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-PS: Pervasive Systems, EWI-CAES: Computer Architecture for Embedded Systems
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:SeaSTAR: Underwater Monitoring Platforms
ID Code:24490
Deposited On:11 July 2014
More Information:statisticsmetis

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