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Design of Inertial Measurement Unit in Attitude and Heading Reference System for Real-Time Maneuver Monitoring by Using Kalman Filter

The presence of white noise originates complexity in the sensor acquisition process for any aviation technology. A miniature error in sensor data acquisition can create a colossal impact, as the sensor pitch varies within 15 degrees. Fluctuations in sensor data acquisition can be calibrated through implementing conventional signal conditioning techniques, nevertheless, the existing white noise can not be eliminated. This research has investigated the performance of the Kalman filter in eliminating such white noise in the sensor data acquisition process. Here, the Kalman filter is used in conjunction with the Inertial Measurement Unit (IMU). The hybrid filtering approach produces a smooth reading of the aircraft’s roll, pitch, and yaw readings, thus simulating a very accurate altitude simulation. This investigation suggests Kalman filter can significantly reduce white noise in such a sensitive application in the aviation field.