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.

中文翻译：

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多源融合室内定位误差模型与仿真

无缝定位服务是建设智慧城市的关键。在多源融合室内定位系统中，为定位源的部署提供引导信息是一项关键技术，可以优化基础设施资源，提供更高的定位精度。应扩展接收信号强度（RSS）指纹和行人航位推算（PDR）等单源定位误差模型，以满足多源室内定位对定位误差估计的要求。本文提出了一种结合RSS指纹和PDR定位误差模型进行融合定位误差模拟的模型，它对 PDR 和 RSS 指纹定位结果进行加权，并根据它们的定位方差计算融合定位的均方误差。该模型还用于建立室内定位仿真系统。为了验证所提出的模型，进行了一个实验，将使用融合定位的实际定位误差与仿真模型的误差进行了比较。结果表明，实际定位误差曲线与模型预测的误差曲线是一致的。因此，所提出的误差模型为优化定位源的部署提供了解决方案。进行了一个实验，将使用融合定位的实际定位误差与模拟模型的误差进行了比较。结果表明，实际定位误差曲线与模型预测的误差曲线是一致的。因此，所提出的误差模型为优化定位源的部署提供了解决方案。进行了一个实验，将使用融合定位的实际定位误差与模拟模型的误差进行了比较。结果表明，实际定位误差曲线与模型预测的误差曲线是一致的。因此，所提出的误差模型为优化定位源的部署提供了解决方案。