Multi-level MEKF-based State Estimation of Micro-UAVs
Aiming at the problem that it is difficult for conventional algorithms to ensure the accu-racy and real-time of UAV state information resolution as the low cost inertial measurement units are in poor accuracy and weak in stability when micro-UAVs operate in when GPS-denied environment.A multi-level multiplicative extended Kalman filter(MEKF)state estimation algorithm based on the fu-sion of IMU and optical flow sensors is proposed.Firstly,the magnetometer,gyroscope and accelerome-ter data are fused to achieve attitude estimation;secondly,the attitude estimation,acceleration and opti-cal flow data are used to achieve the velocity estimation;finally,the integral of the velocity estimation is fused with the altitude data to achieve position estimation.The experiment results show that the algo-rithm achieves faster and more reliable state estimation than that of the traditional algorithms.
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