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INS/GPS Fusion for Navigation of Unmanned Aerial Vehicles

Sanketh Ailneni

Abstract


This paper presents fusion of inertial navigation system (INS) and global positioning system (GPS) for estimating position, velocities, attitude and heading of an unmanned aerial vehicle (UAV). A 15 state extended Kalman filter (EKF) and a split architecture consisting of 6 state non-linear complementary filter (NCF) and 9 state EKF are investigated in detail. In both these fusion architectures GPS and IMU consisting of 3 axis accelerometers, 3 axis rate gyros and 3 axis magnetometer have been fused in open loop fashion (loosely coupled) to estimate the navigation states. These architectures have been implemented in MATLAB/SIMULINK environment and evaluated in closed loop guidance of MAV with Software-In-Loop-Simulation (SILS) setup. Furthermore, the 15-state EKF algorithm is validated with flight test data obtained from onboard data logger using an off-the shelf autopilot board (Ardupilot Mega APM-2.5) for UAV.

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References


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DOI: http://dx.doi.org/10.21535%2FProICIUS.2013.v9.422

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