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Open AccessArticle

A Localization and Tracking Approach in NLOS Environment Based on Distance and Angle Probability Model

1
Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2
College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(20), 4438; https://doi.org/10.3390/s19204438
Received: 11 September 2019 / Revised: 8 October 2019 / Accepted: 9 October 2019 / Published: 14 October 2019
(This article belongs to the Special Issue Sensors Localization in Indoor Wireless Networks)
In this paper, an optimization algorithm is presented based on a distance and angle probability model for indoor non-line-of-sight (NLOS) environments. By utilizing the sampling information, a distance and angle probability model is proposed so as to identify the NLOS propagation. Based on the established model, the maximum likelihood estimation (MLE) method is employed to reduce the error of distance in the NLOS propagation. In order to reduce the computational complexity, a modified Monte Carlo method is applied to search the optimal position of the target. Moreover, the extended Kalman filtering (EKF) algorithm is introduced to achieve localization. The simulation and experimental results show the effectiveness of the proposed algorithm in the improvement of localization accuracy. View Full-Text
Keywords: NLOS; EKF; localization; probability model; MLE NLOS; EKF; localization; probability model; MLE
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MDPI and ACS Style

Tian, X.; Wei, G.; Wang, J.; Zhang, D. A Localization and Tracking Approach in NLOS Environment Based on Distance and Angle Probability Model. Sensors 2019, 19, 4438.

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