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In this study, we design connected multiple drones through electromagnets, and it requires an attitude estimation method that does not use magnetic sensors. In order to solve this problem, we propose an extended Kalman filter-based attitude estimation method based on the multiple global positioning system (GPS) to substitute the magnetic sensor. Additionally, we demonstrate that combining velocity vectors allows for highly accurate attitude estimation. We compare the estimation accuracy and stability of attitude estimation in simulation and real environments using two types of experiments. It is confirmed that the accuracy of yaw angle estimation of the proposed method is improved 36.1% in simulation and 29.7% in the real environments compared to conventional extended Kalman filter.

Attitude estimation of connected drones based on extended Kalman filter under real outdoor environments