SHI Yun-fei, HAO Yong-sheng, LIU De-liang, WANG Bo. RSS-assisted ray tracing indoor positioning algorithm[J]. JOURNAL OF SIGNAL PROCESSING, 2018, 34(10): 1259-1266. DOI: 10.16798/j.issn.1003-0530.2018.10.015
Citation: SHI Yun-fei, HAO Yong-sheng, LIU De-liang, WANG Bo. RSS-assisted ray tracing indoor positioning algorithm[J]. JOURNAL OF SIGNAL PROCESSING, 2018, 34(10): 1259-1266. DOI: 10.16798/j.issn.1003-0530.2018.10.015

RSS-assisted ray tracing indoor positioning algorithm

  • For indoor positioning, when the signal is affected by NLOS and multipath propagation, an RSS-assisted Ray-Tracing indoor location algorithm is proposed. Improve the positioning accuracy of the TOA and DOA indoor wireless signal Ray-tracing model based on the virtual base station method, the RSS signal measurement optimization algorithm is used to achieve co-location of TOA, DOA and RSS, improve indoor multipath and NLOS environments, reduce the complexity of the algorithm, improve the ability of the algorithm to process multiple scattering signals and reduce the dependence on the base station. The application environment is more extensive. First obtain the possible location of the signal source via RSS, then use the Ray-Tracing principle and use the virtual base station to convert the NLOS path location problem to the NLOS location problem, using TOA and DOA for direct, transmission, reflection and diffraction situation is analyzed and modeled. Finally, the possible locations are screened using the least square method to obtain the final location of the signal source. Simulation results show that the algorithm has higher positioning accuracy.
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