Abstract: An Indoor Localization Simulation Platform for Localization Accuracy Evaluation

Feng, Guangsheng; Wang, Huiqiang; Lin, Junyu; Liu, Jingyao; Lv, Hongwu; Zhao, Shuai

doi:10.1109/sahcn.2018.8397158

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…It is therefore necessary to establish an accurate indoor positioning error model for optimizing a positioning source deployment plan. 3 The error model can provide a technical basis for the optimal layout of the positioning infrastructure and explore the factors affecting the positioning accuracy. [4][5][6] There are many articles about the error models for the RSS fingerprint and the PDR, but few focused on the theoretical analysis of the positioning accuracy for a fusion model of RSS fingerprint and PDR.…”

Section: Introductionmentioning

confidence: 99%

Error model and simulation for multisource fusion indoor positioning

Tao

et al. 2021

Int J of Intelligent Sys

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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

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Section: Introductionmentioning

confidence: 99%

Error model and simulation for multisource fusion indoor positioning

Tao

et al. 2021

Int J of Intelligent Sys

View full text Add to dashboard Cite

show abstract

Abstract: An Indoor Localization Simulation Platform for Localization Accuracy Evaluation

Cited by 1 publication

References 9 publications

Error model and simulation for multisource fusion indoor positioning

Error model and simulation for multisource fusion indoor positioning

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