
AbstractThe problem of gyrocompassing using inertial sensors, i.e., gyros and accelerometers, is addressed. North finding, with an order of accuracy of one arc-min, is not only required for the initial alignment of inertial navigation systems, but also has a critical role to play in the guidance and navigation of ships that navigate for long periods of time. In this work, after extracting the error model of an inertial navigation system and augmenting it with the error model of inertial sensors, a processing algorithm based on the Kalman filter is designed and simulated to process the navigation system velocity error, and to estimate and correct tilt and heading errors along with gyro drifts and accelerometer biases. It is verified that using gyros with drift stability of 0.01 deg/hr, and accelerometers with bias stability of 100 μg, the true north direction can be determined with an accuracy of about five arc-mins.
Kalman filter, Heading error, Data fusion, Inertial navigation, Gyrocompassing
Kalman filter, Heading error, Data fusion, Inertial navigation, Gyrocompassing
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