A Kalman Filter Based Attitude Heading Reference System Using a Low Cost Inertial Measurement Unit

Abstract

This paper describes the development of a sensor fusion algorithm-based Kalman filter architecture, for an Attitude Heading Reference System (AHRS) based on a low cost Inertial Measurement Unit (IMU). The system is verified with real time manual flight testing as well as autonomous waypoint flight testing. A low cost IMU uses Micro-ElectricalMechanical System(MEMS) technology using inexpensive, compact, and low grade sensors. The use of low cost IMUs is primarily targeted towards Unmanned Aerial Vehicle (UAV) applications due to the requirements for small package size, low energy consumption, and high sampling rate. The high dynamics nature of smaller airframes, coupled with the typical vibration induced noise of UAVs require an efficient, reliable, and robust Attitude Heading Reference System (AHRS) for vehicle control. To eliminate the singularities at ±90◦ and to maximize the computational efficiency, quaternions are used for state attitude representation.