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An Efficient Approach for Rigid Body Localization via a Single Base Station Using Direction of Arrive Measurement

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Ad Hoc Networks (ADHOCNETS 2019)

Abstract

Rigid bodies are objects whose profile will not change after moving or being forced. A framework of rigid body localization (RBL) is to estimate the position and the orientation of a rigid object. In a wireless node network (WSN) based RBL approach, a few wireless nodes are mounted on the surface of the rigid target. Even though the position of the rigid body is unknown, we know how the nodes are distributed, which means that the topology of the nodes is known. Recently, a novel RBL scheme is studied, in which the rigid target is localized with just one single base station (BS) by measuring the angles between the BS and the positions of wireless nodes in the current frame, i.e., direction of arrival (DOA). However, the DOA-based RBL model is highly nonlinear and existing heuristic algorithms are generally time-consuming. In this paper, we intend to find the optimal solution of the 3-D positions of wireless nodes by fusing the topology information and DOA measurements with Newton’s Iteration algorithm (NIA). Then, the rotation matrix and the translation vector can be obtained by the unit quaternion (UQ) method with the 3-D positions of wireless nodes, which completes the RBL task. Finally, we evaluate the proposed NIA-based RBL performance in terms of the root mean squared error (RMSE), as well as the computation costs.

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Funding

This work is partly supported by National Natural Science Foundation of China (No. 61703185 and No. 61701197), Natural Science Foundation of Jiangsu Province (No. BK20180597), China Postdoctoral Science Foundation (No. 2018M641354).

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Correspondence to Biao Zhou .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wu, S., Ai, L., Zhan, J., Yang, L., Wu, Q., Zhou, B. (2019). An Efficient Approach for Rigid Body Localization via a Single Base Station Using Direction of Arrive Measurement. In: Zheng, J., Li, C., Chong, P., Meng, W., Yan, F. (eds) Ad Hoc Networks. ADHOCNETS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 306. Springer, Cham. https://doi.org/10.1007/978-3-030-37262-0_18

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  • DOI: https://doi.org/10.1007/978-3-030-37262-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37261-3

  • Online ISBN: 978-3-030-37262-0

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