Real-Time Localization of Transmission Sources by a Formation of Helicopters Equipped with a Rotating Directional Antenna V´ aclav Pritzl 1 , Luk´ aˇ s Vojtˇ ech 2 , Marek Neruda 2 , and Martin Saska 1(B ) 1 Department of Cybernetics, Czech Technical University in Prague, Prague, Czech Republic {pritzvac,martin.saska}@fel.cvut.cz 2 Department of Telecommunication Engineering, Czech Technical University in Prague, Prague, Czech Republic {vojtecl,marek.neruda}@fel.cvut.cz http://mrs.felk.cvut.cz/ Abstract. This paper proposes a novel technique for radio frequency transmission sources (RFTS) localization in outdoor environments using a formation of autonomous Micro Aerial Vehicles (MAVs) equipped with a rotating directional antenna. The technique uses a fusion of received signal strength indication (RSSI) and angle of arrival (AoA) data gained from dependencies of RSSI on angle measured by each direc- tional antenna. An Unscented Kalman Filter (UKF) based approach is used for sensor data fusion and for estimation of RFTS positions during each localization step. The proposed method has been verified in simula- tions using noisy and inaccurate measurements and in several successful real-world outdoor deployments. Keywords: RFID localization · Micro Aerial Vehicles · Unscented Kalman Filter · Directional antenna · Radio frequency transmission sources localization 1 Introduction Fast and precise radio frequency (RF) transmission sources localization is a chal- lenging task required in numerous application scenarios. Active radio frequency identification (RFID) tags are commonly used in many industrial applications, such as finding working tools or machinery in construction sites and localiza- tion and identification of stock items in warehouses. RFIDs are conveniently used in agriculture for livestock tracking in order to monitor cattle health, pre- vent cattle rustling or localize lost animals. Tracking of endangered species is another widespread use of RFID tags. Furthermore, RF localization brings an undeniable benefit to searching for people during natural disasters or search c  Springer Nature Switzerland AG 2019 J. Mazal (Ed.): MESAS 2018, LNCS 11472, pp. 335–350, 2019. https://doi.org/10.1007/978-3-030-14984-0_25