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More accurate Received Signal Strength Indicator (RSSI) calibration which is optimized via Gaussian filtering, together with the environment-dependent attenuation coefficient optimization, results in a more precise hybrid model in the complicated indoor environment. Experiment results show that the difference between the estimated results and the measured samples is less than 0.25[Formula: see text]m as the target node and reference node is less than 1.5[Formula: see text]m far from each other. As the distance increases to more than 1.5[Formula: see text]m, the relative difference between the estimated values and the measured ones decreases to 7.8% at most, satisfying the requirements for indoor positioning applications.<\/jats:p>","DOI":"10.1142\/s0218001418540149","type":"journal-article","created":{"date-parts":[[2017,10,19]],"date-time":"2017-10-19T05:13:27Z","timestamp":1508390007000},"page":"1854014","source":"Crossref","is-referenced-by-count":6,"title":["Research on an Adaptive Algorithm for Indoor Bluetooth Positioning"],"prefix":"10.1142","volume":"32","author":[{"given":"Heng","family":"Luo","sequence":"first","affiliation":[{"name":"Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, No. 1, Kerui Road, Suzhou New District, Suzhou, P. R. 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