Radio Frequency Identification target location based on the Unmanned Aerial Vehicle

Abstract

Due to the complex environment, the traditional Radio Frequency Identification (RFID) localization algorithm is cumbersome, the system localization accuracy is low, and the calculation time is relatively complex, an RFID localization algorithm based on sequential Kalman filtering has been proposed in this paper. Through the flight of sequential points, The Unmanned Aerial Vehicle (UAV) with the reader collects the Received Signal Strength Indication (RSSI) data dealt with mixed filtering of the target in the scene, after obtaining the coordinates according to the three-ball intersection method, and then using the Unscented Kalman Filter (UKF) algorithm to generate the estimation equation, thereby determining the position trajectory information to estimate. The results show that compared with other positioning methods the system has higher mobility and improved positioning accuracy with an average of 13.15%. At the same time, due to the real-time and flexibility of drones, this system can also be applied to more diverse scenarios. And the algorithm operation time is 1.15 s and it is suitable for UAVs scenarios.