Single Anchor Location System using Ultra-wideband
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Date
2023-12
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Publisher
The Ohio State University
Abstract
This thesis introduces a real-time location system (RTLS) employing a hidden Markov model
(HMM) map-matching scheme. In the hidden Markov model, hidden states are generated
within the grids of the area of interest. At each time interval, two types of data are collected:
the distance between a single anchor and the object, and the heading angle of the object. The
object's heading angle is employed to compute the prior distribution of the object's next
position based on its past position. The distance between the object and a single anchor is
employed to calculate the observation likelihood of the current position using a normal
distribution. By utilizing two probability matrices, the maximum likelihood of the current
position of the object in the hidden Markov model state can be generated. Consequently,
recursive Bayesian filters can leverage these estimated positions to create a map for the RTLS.
Description
Keywords
Location System, UWB