Abstract
Wireless sensor networks (WSNs) have the focus of research in recent years. Moreover, positioning is very important for wireless sensor networks. However, the positioning accuracy still has large error in the case of non-line-of-sight. In this paper, we propose an improved Kalman filter algorithm to reduce the influence of NLOS error. For the case of NLOS, the measurement residual Ei(k) is updated firstly. This method can effectively reduce the NLOS error, which makes the positioning result more accurate. The simulation results show that the proposed localization algorithm can accurately apply to the normal NLOS location problem.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China under Grant No. 61403068; Natural Science Foundation of Hebei Province under Grant No. F2015501097 and F2016501080; Scientific Research Fund of Hebei Provincial Education Department under Grant No. Z2014078; NEUQ internal funding under Grant No. XNB2015009 and XNB2015010.
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Cheng, L., Shao, Y., Wang, Y. (2017). A Novel Kalman Filter Based NLOS Localization Method for Wireless Sensor Networks. In: Sun, X., Chao, HC., You, X., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2017. Lecture Notes in Computer Science(), vol 10602. Springer, Cham. https://doi.org/10.1007/978-3-319-68505-2_42
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DOI: https://doi.org/10.1007/978-3-319-68505-2_42
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