Mobile Positioning in Mixed LOS/NLOS Conditions Using Modified EKF Banks and Data Fusion Method

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概要

• 論文の詳細を見る

• A novel method is proposed to track the position of MS in the mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions in cellular network. A first-order markov model is employed to describe the dynamic transition of LOS/NLOS conditions, which is hidden in the measurement data. This method firstly uses modified EKF banks to jointly estimate both mobile state (position and velocity) and the hidden sight state based on the the data collected by a single BS. A Bayesian data fusion algorithm is then applied to achieve a high estimation accuracy. Simulation results show that the location errors of the proposed method are all significantly smaller than that of the FCC requirement in different LOS/NLOS conditions. In addition, the method is robust in the parameter mismodeling test. Complexity experiments suggest that it supports real-time application. Moreover, this algorithm is flexible enough to support different types of measurement methods and asynchronous or synchronous observations data, which is especially suitable for the future cooperative location systems.

• （社）電子情報通信学会の論文
• 2009-04-01

著者

• WU Lenan

  School of Information Science and Engineering, Southeast University

• Wu Lenan

  School Of Information Science And Engineering Southeast University

• CHEN Liang

  School of Information Science and Engineering, Southeast University

• Chen Liang

  School Of Information Science And Engineering Southeast University

関連論文

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• Mobile Positioning in Mixed LOS/NLOS Conditions Using Modified EKF Banks and Data Fusion Method
• Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks
• Sparse Recovery Algorithms for Pilot Assisted MIMO OFDM Channel Estimation
• Application of Compressive Projection Principal Component Analysis to MIMO Channel Feedback Scheme

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