Nine degrees of freedom (DOF) inertial measurement units (IMUs) comprised of three-axis magnetometers, three-axis accelerometers, and three-axis angular rate sensors are commonly used in attitude and heading reference systems (AHRSs). Two classes of AHRSs exist: systems that estimate true-North heading and systems that estimate magnetic-North heading. True-North heading AHRSs require high-end angular rate sensors which are sensitive enough to dynamically estimate Earth-rate (typically fiber-optic and ring-laser gyros), while magnetic-North AHRSs employ gyros that are not sensitive enough to dynamically estimate Earth-rate (i.e. all MEMS gyros). Thus, magnetic-North AHRSs employ magnetometers for estimating heading. This paper will focus on this class of magnetic-North AHRSs. These systems fuse IMU measurements to generate estimates of the instrument's roll, pitch, and magnetic heading. However, their accuracy is limited by sensor measurement bias that is unknown a priori. Hence, accurate sensor bias estimation and compensation is essential for true attitude estimation. This paper reports a novel adaptive sensor bias observer for sensor measurement biases in 9-DOF IMUs. The algorithm requires smaller angular movements of the instrument than other reported sensor bias calibration methods, does not require a priori knowledge of local fields like the local magnetic field or the local gravity vector, and does not require knowledge of the attitude of the instrument. Stability proofs, preliminary simulations, and a full-scale vehicle experimental evaluation are reported.

This paper reports a novel stable adaptive attitude estimator and preliminary simulation results of a true-North gyrocompass system employing the attitude adaptive identifier and a commercially available low-cost inertial measurement unit (IMU) comprising a 3-axis fiber optic gyroscope (FOG) with a 3-axis micro-electro-mechanical systems (MEMS) accelerometer. Optical North-seeking gyrocompass systems typically employ a microprocessor system to sample the low-level raw sensor values for angular-rate and linear-acceleration at a high sampling rate and estimate true-North heading, pitch, and roll. This paper reports the first adaptive attitude estimator on SO (3) which utilizes 3-axis angular-rate sensor data and 3-axis linear acceleration sensor data to estimate the instrument's 3-degrees of freedom (DOF) attitude (roll, pitch, and heading) without using magnetometry of the Earth's magnetic field. A stability proof and preliminary numerical simulation results are reported. The simulation results for a rotating IMU configuration are promising, and further experimental evaluation and extension of the algorithm for the case of a translating IMU configuration typically found on moving robotic vehicles are needed.

Six-degree of freedom (DOF) inertial measurement units (IMUs) are widely used for attitude estimation. However, such systems' accuracy is limited by the accuracy of calibration of bias, scale factors, and non-orthogonality of sensor measurements. This paper reports a stable adaptive estimator of measurement bias in six-DOF IMUs and preliminary simulation results employing a commercially available IMU comprising a 3-axis fiber optic gyroscope (FOG) with a 3-axis micro-electro-mechanical systems (MEMS) accelerometer. A stability proof of the adaptive estimator and preliminary numerical simulation results are reported. The simulation results for a rotating IMU configuration are promising, and further experimental evaluation and extension of the algorithm for the case of a translating IMU configuration typically found on moving robotic vehicles are needed.