AMarkovModel for Dynamic Behavior of ToA-Based Ranging in Indoor Localization

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, the authors 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.