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In recent years, much attention has been paid to wireless localization schemes that exploit receptions of messages sent by a mobile unit. However, existing methods assume an accurate knowledge of the location of the mobile unit and a precise propagation model of the actual radio environment. By getting rid of these two requirements, our proposed localization algorithms make mobility-assisted localization far more practical as we do not need to equip the mobile unit with a global positioning system or run a time-consuming campaign to survey radio environment. LEMOn estimates the position of target nodes by using known locations of a small set of fixed anchor nodes while receiving messages sent from a mobile unit from unknown arbitrary locations. LEMOn-M, on the other hand, solves the localization matching problem by mapping an arbitrary number of target nodes to the known set of locations. Both algorithms first estimate an inter-node distance using a similarity between received signal strength indicators of beacons received from the mobile unit. The conventional location estimators are then employed to localize target nodes with an unknown location. The obvious examples of real-world applications include but are not limited to unmanned aerial vehicle assisted wireless sensor networks and indoor IoT systems. The various simulations show that the two algorithms achieve a very high localization accuracy even in harsh radio environments while static localization techniques fail.

LEMOn: Wireless Localization for IoT Employing a Location-Unaware Mobile Unit