Title :
Square-Root Unscented Kalman Filtering Based Localization and Tracking in the Internet of Things
Author :
Guo, Junqi ; Zhang, Hongyang ; Sun, Yunchuan ; Bie, Rongfang
Author_Institution :
Coll. of Inf. Sci. & Technol., Beijing Normal Univ., Beijing, China
Abstract :
Target localization and tracking in the Internet of Things (IoT) environment have been paid more and more attention recently. The knowledge and information generated from wireless sensor nodes of the IoT make huge contributions to localization and tracking of targets with high mobility. This paper presents a square-root unscented Kalman filtering (SR-UKF) based localization and tracking algorithm for mobile target in an IoT environment. First, a localization initialization model is proposed for an IoT scenario. Then, according to information of neighboring sensor nodes, we employ the SR-UKF idea for the further localization and tracking of the target. Simulation results demonstrate that the proposed algorithm achieves lower localization and tracking error under the same computational complexity, compared with some conventional extended Kalman filtering (EKF) or UKF based methods. The proposed algorithm is of great significance in the field of IoT information processing.
Keywords :
Internet; Kalman filters; nonlinear filters; target tracking; wireless sensor networks; EKF; Internet of things; IoT environment; SR-UKF; computational complexity; extended Kalman filtering; information processing; neighboring sensor nodes; square-root unscented Kalman filtering; target localization; target tracking; wireless sensor nodes; Equations; Kalman filters; Mathematical model; Mobile communication; Target tracking; Vectors; Internet of Things (IoT); localization; square-root unscented Kalman filtering (SR-UKF); tracking;
Conference_Titel :
Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on
Conference_Location :
Liverpool
Print_ISBN :
978-1-4673-2172-3
DOI :
10.1109/TrustCom.2012.265