Improved D/TA and Information Fusion Based on HMM Indoor Localization

Abstract:

This paper describes an efficient Bayesian framework for localization based on Ultra-wide Bandwidth (UWB) system. Approximate grid-based method based on the Hidden Markov Model (HMM) is an effective method to estimate the position of the Moving Terminal (MT) with the mixed line-of-sight/non-line-of-sight (LOS/NLOS) situation. This article proposes an algorithm by modifying the Position Transition Probability (PTP) according to the practical dynamic model and uses the information fusion effectively. We compare the Maximum Likelihood (ML) estimation with Detection/Tracking Algorithm (D/TA) estimation and its improved algorithm by simulation, in which the localization to an identical trajectory has been tested. The results of the analysis show that the proposed method has better accuracy and stability.

• Periodical: Applied Mechanics and Materials (Volumes 373-375)
• Pages: 916-921
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.373-375.916
• Online since: August 2013
• Authors: Jing Yu Ru, Cheng Dong Wu, Yun Zhou Zhang, Rong Fen Gong, Peng Da Liu
• Keywords: Detection/Tracking Algorithm, Hidden Markov Model (HMM), Indoor Localization, Information Fusion, Moving Terminal, RSS, Ultra-Wide Bandwidth

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