Remote Sensing (Jan 2023)

Multi-Level Fusion Indoor Positioning Technology Considering Credible Evaluation Analysis

  • Lu Huang,
  • Baoguo Yu,
  • Shitong Du,
  • Jun Li,
  • Haonan Jia,
  • Jingxue Bi

DOI
https://doi.org/10.3390/rs15020353
Journal volume & issue
Vol. 15, no. 2
p. 353

Abstract

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Aiming at the problems of the low robustness and poor reliability of a single positioning source in complex indoor environments, a multi-level fusion indoor positioning technology considering credible evaluation is proposed. A multi-dimensional electromagnetic atlas including pseudolites (PL), Wi-Fi and a geomagnetic field is constructed, and the unsupervised learning model is used to sample in the latent space to achieve a feature-level fusion positioning. A location credibility evaluation method is designed to improve the credibility of the positioning system through a multi-dimensional data quality evaluation and heterogeneous information auxiliary constraints. Finally, a large number of experiments were carried out in the laboratory environment, and, finally, about 90% of the positioning error was better than 1 m, and the average positioning error was 0.56 m. Compared with several relatively advanced positioning methods (Inter-satellite CPDM/Epoch-CPDS/Z-KPI) at present, the average positioning accuracy is improved by about 56%, 83.5% and 82.9%, respectively, which verifies the effectiveness of the algorithm. To verify the effect of the proposed method in a practical application environment, the proposed positioning system is deployed in the 2022 Winter Olympics venues. The results show that the proposed method has a significant improvement in the positioning accuracy and continuity.

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