Abstract
In recent years, Wireless Access Point (WAP)-based Received Signal Strength Indication (RSSI) indoor localization technology has been of intriguing interest to deduce the coordinates of an object or an observer in the scene with RSSI being collected by various WAPs in a Range of Interest (ROI). The Radio Map construction by fingerprints is of great importance for indoor localization. Existing methods of Radio Map construction have encountered bottlenecks in this area, which will limit the application of indoor localization technology due to the deployment is massive and cumbersome. The spatial correlation between RSSI observations is adopted and the manifold alignment algorithm will be adopted to locate the user’s current location without a complete Radio Map so as to reduce the requirements of the calibration fingerprints. Simulated Radio Map (SRM) scheme and Plan Coordinate (PC) scheme will be proposed and simulated separately to verify the correctness and efficiency of the proposed scheme.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China (61771186), Postdoctoral Research Project of Heilongjiang Province (LBH-Q15121), University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province (UNPYSCT-2017125).
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Ji, P., Qin, D., Feng, P., Zhang, Y. (2018). Manifold Alignment-Based Radio Map Construction in Indoor Localization. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_33
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DOI: https://doi.org/10.1007/978-3-030-00557-3_33
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