1. Tailored Hidden Markov Model: A Tailored Hidden Markov Model Optimized for Cellular-Based Map Matching.
- Author
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Chen, Renhai, Yuan, Shimin, Ma, Chenlin, Zhao, Huihui, and Feng, Zhiyong
- Subjects
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HIDDEN Markov models , *LOCALIZATION (Mathematics) , *MARKOV processes , *CELL phones , *MEASUREMENT errors , *GLOBAL Positioning System - Abstract
Although the GPS-based positioning is ubiquitous for its high precision, the high power consumption brought by the high sampling frequency and the poor GPS signal penetration limits its availability in locating low-power mobile devices (especially mobile phones). As a promising complement, the cellular-based positioning has attracted great attention since it consumes much less power as well as its higher availability. However, the sparsity of cellular-based data (due to lower sampling rate) and large localization errors make the measurement accuracy becomes the main challenge of the cellular-based positioning. hidden Markov model can well solve the problem of positioning error of GPS data, but it is less accurate when applied to map matching of cellular-base data. Therefore, to improve accuracy, in this article, we propose a novel algorithm called the tailored hidden Markov model (THMM) that is optimized for the cellular-based data. Specifically, the geometric, the topological, and the probabilistic characteristics have been considered and fully exploited in the THMM design. Our proposed schemes are evaluated using real-world motor vehicle movement trajectories collected in Tianjin and the experimental results are encouraging compared with the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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