A Markov Model for Dynamic Behavior of ToA-Based Ranging in Indoor Localization. (2008)

• Record Type: Journal Article
• Authors: Heidari Heidari, Mohammad Mohammad; Pahlavan Pahlavan, Kaveh Kaveh
• Other Names: Gezici Gezici Sinan Sinan Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/241069
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : The existence of undetected direct path (UDP) conditions causes occurrence of unexpected large random ranging errors which pose a serious challenge to precise indoor localization using time of arrival (ToA). Therefore, analysis of the behavior of the ranging error is essential for the design of precise ToA-based indoor localization systems. In this paper, we propose a novel analytical framework for the analysis of the dynamic spatial variations of ranging error observed by a mobile user based on an application of Markov chain. The model relegates the behavior of ranging error into four main categories associated with four states of the Markov process. The parameters of distributions of ranging error in each Markov state are extracted from empirical data collected from a measurement calibrated ray tracing (RT) algorithm simulating a typical office environment. The analytical derivation of parameters of the Markov model employs the existing path loss models for the first detected path and total multipath received power in the same office environment. Results of simulated errors from the Markov model and actual errors from empirical data show close agreement.