Error model and simulation for multisource fusion indoor positioning

Haojun Ai*, Jingjie Tao*, Shan Ai*, Tianshui Xu, Ning Li, Kaifeng Tang, Sheng Zhang, Yuhong Yang, Shengchen Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Seamless positioning services are of a critical concern in building smart cities. In a multisource fusion indoor positioning system, providing the guidance information for the deployment of positioning sources is a key technology, which can optimize the infrastructure resources to provide higher positioning accuracy. The error models of single-source positioning such as the received signal strength (RSS) fingerprint and the pedestrian dead reckoning (PDR) should be extended to meet the requirement of multisource indoor positioning for positioning error estimation. This paper proposes a model that combines the RSS fingerprint and PDR positioning error models for fusion positioning error simulation, which weights the PDR and RSS fingerprint positioning results and calculates the mean square error for the fusion positioning according to their positioning variances. This model is also used to establish an indoor positioning simulation system. To validate the proposed model, an experiment is performed which compared the actual positioning errors using the fusion positioning with the errors of the simulate model. The results show that the actual positioning error curves and the error curve predicted by the model are consistent. As a result, the proposed error model provides a solution for optimizing the deployment of positioning sources.

Original languageEnglish
Pages (from-to)2219-2241
Number of pages23
JournalInternational Journal of Intelligent Systems
Issue number3
Early online date28 Nov 2021
Publication statusPublished - Mar 2022


  • error model
  • fingerprint
  • indoor positioning simulation system
  • PDR

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