RSSI-based Indoor Localization Using RSSI-with-Angle-based Localization Estimation Algorithm

For the scenarios of indoors localization and tracking, the solutions generally need complex infrastructure because they would require either a grid of antennas, each having a well-known position (proximity based approach), or a sophisticated algorithm that uses scene fingerprint to estimate the location or the zone of an object by matching the online measurement with the closest offline measurement. Those techniques may not be available in unknown zones, which will make it difficult to locate a lost node. In this paper, with no additional hardware costs, we propose a new RSSIbased approach in order to find a lost node using a known node. By rotating the known node at the same spot we can collect different RSSI for different polar angles. Two pairs of angles with the strongest RSSI will indicate the main lobes of the radiation pattern, namely, zone of the unknown node. Experimental results illustrate a very close estimation of the unknown node zone, reducing up to 84% of the zone uncertainty.