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Massive MIMO for High-Accuracy Target Localization and Tracking

High-accuracy target localization and tracking have been widely used in the modern navigation system. However, most of the methods such as global positioning system (GPS) are highly dependent on time measurement accuracy, which prevents them from achieving high accuracy in practice. Time reversal (T...

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Bibliographic Details
Published in:IEEE internet of things journal 2021-06, Vol.8 (12), p.10131-10145
Main Authors: Zeng, Xiaolu, Zhang, Feng, Wang, Beibei, Liu, K. J. Ray
Format: Article
Language:English
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Summary:High-accuracy target localization and tracking have been widely used in the modern navigation system. However, most of the methods such as global positioning system (GPS) are highly dependent on time measurement accuracy, which prevents them from achieving high accuracy in practice. Time reversal (TR)-based technique has been shown to be able to achieve centimeter accuracy localization by fully utilizing the focusing effect brought by the massive multipaths naturally existing in a rich scattering environment such as indoor scenarios. By investigating a similar statistical property, this article develops a novel high-accuracy target localization method by using massive MIMO to provide massive signal components. We first observe that the statistical autocorrelation of the received energy physically focuses into a beam around the receiver exhibiting a sinc-like distribution in the far-field scenario. By leveraging such a distribution of the focusing beam, an effective way to estimate the relative moving speed of the target with respect to a single base station is proposed. We also obtain the absolute moving speed and subsequently track the target accurately by associating the speed estimation results and geometrical relationship of multiple stations. The theoretical analysis on the error in the speed and localization estimation validated by numerical simulation results show that the proposed system can achieve decimeter accuracy for target localization and tracking.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2021.3050720