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Received signal strength-based indoor localization using a robust interacting multiple model-extended Kalman filter algorithm.

, , , , and . Int. J. Distributed Sens. Networks, (2017)

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Data Fusion With Model-Based Machine Learning For Weighted Least Squares Based Positioning., and . ICSPCS, page 1-6. IEEE, (2020)Potential Game for Energy-Efficient RSS-Based Positioning in Wireless Sensor Networks., , and . IEEE J. Sel. Areas Commun., 33 (7): 1394-1406 (2015)Supermodular game for energy efficient TOA-based positioning., , and . SPAWC, page 35-39. IEEE, (2012)LACFA: an algorithm for localization aware cluster formation in wireless sensor networks., , and . EURASIP J. Wirel. Commun. Netw., (2011)Supermodular Game for Power Control in TOA-Based Positioning., , and . IEEE Trans. Signal Process., 61 (12): 3246-3259 (2013)A Data-Driven Factor Graph Model for Anchor-Based Positioning., and . Sensors, 23 (12): 5660 (2023)Assessment of RSS model calibration with real WLAN devices., , , and . ISWCS, page 746-750. IEEE, (2015)Performance analysis of cooperative and range based localization algorithms for Zigbee and 802.15.4a Wireless Sensor Networks., and . PIMRC, page 1996-2001. IEEE, (2010)Received signal strength-based indoor localization using a robust interacting multiple model-extended Kalman filter algorithm., , , , and . Int. J. Distributed Sens. Networks, (2017)Energy-efficient positioning in sensor networks by a game theoretic approach., , and . EUSIPCO, page 2014-2018. IEEE, (2011)