Research Article
An Efficient Approach for Rigid Body Localization via a Single Base Station Using Direction of Arrive Measurement
@INPROCEEDINGS{10.1007/978-3-030-37262-0_18, author={Shenglan Wu and Lingyu Ai and Jichao Zhan and Le Yang and Qiong Wu and Biao Zhou}, title={An Efficient Approach for Rigid Body Localization via a Single Base Station Using Direction of Arrive Measurement}, proceedings={Ad Hoc Networks. 11th EAI International Conference, ADHOCNETS 2019, Queenstown, New Zealand, November 18--21, 2019, Proceedings}, proceedings_a={ADHOCNETS}, year={2020}, month={1}, keywords={Rigid body localization Single base station Direction of arrival Newton’s iteration algorithm The unit quaternion method}, doi={10.1007/978-3-030-37262-0_18} }- Shenglan Wu
Lingyu Ai
Jichao Zhan
Le Yang
Qiong Wu
Biao Zhou
Year: 2020
An Efficient Approach for Rigid Body Localization via a Single Base Station Using Direction of Arrive Measurement
ADHOCNETS
Springer
DOI: 10.1007/978-3-030-37262-0_18
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.
