A Hybrid RSS/TOA Algorithm Based on Adaptive EKF for Low-Cost UAV Localization

Abstract

AbstractThis paper addresses the problem of cooperative localization in the global navigation satellite system (GNSS) challenging environment such as urban canyon using received signal strength (RSS) based on Zigbee and time of arrival (TOA) based on ultra-wide bandwidth (UWB). The RSS ranging has advantages in wide range ranging with no cost because the primary responsibility of Zigbee device is communication, but its accuracy needs to be improved. The TOA ranging has a higher ranging accuracy but a shorter range. Considering the characteristics above, a hybrid RSS/TOA algorithm based on inertial navigation system (INS) using sequential extended Kalman filter (EKF) for the position estimation of unmanned aerial vehicle (UAV) at the wide-ranging distance is proposed and further improved by adaptive factor. The experimental results show that the proposed algorithm can achieve a more accurate estimation in short distances and a more robust estimation in long distances.KeywordsUnmanned aerial vehicle (UAV)Time of arrival (TOA)Received signal strength (RSS)Adaptive filteringExtended Kalman filter (EKF)