Improved multi-position calibration for inertial measurement units

Abstract

Calibration of inertial measurement units (IMU) is carried out to estimate the coefficients which transform the raw outputs of inertial sensors to meaningful quantities of interest. Based on the fact that the norms of the measured outputs of the accelerometer and gyroscope cluster are equal to the magnitudes of specific force and rotational velocity inputs, respectively, an improved multi-position calibration approach is proposed. Specifically, two open but important issues are addressed for the multi-position calibration: (1) calibration of inter-triad misalignment between the gyroscope and accelerometer triads and (2) the optimal calibration scheme design. A new approach to calibrate the inter-triad misalignment is devised using the rotational axis direction measurements separately derived from the gyroscope and accelerometer triads. By maximizing the sensitivity of the norm of the IMU measurement with respect to the calibration parameters, we propose an approximately optimal calibration scheme. Simulations and real tests show that the improved multi-position approach outperforms the traditional laboratory calibration method, meanwhile relaxing the requirement of precise orientation control.

Development of a UAV-LiDAR System with Application to Forest Inventory

“…The key properties of the gyroscopes and accelerometers are summarised in Table 1. The IMU has been factory calibrated, however, to confirm the results the IMU was calibrated using the methods outlined in [31]. The GPS observations, recorded at a rate of 5 Hz, are differentially post-processed in order to achieve the highest possible accuracy.…”

On Calibration of Three-Axis Magnetometer

“…In a homogeneous external magnetic field like the geomagnetic field, n m is constant and assumed to have unity norm without loss of generality. The model (1) is a rather general linear transformation that distorts and translates an unit sphere surface into an ellipsoid surface [4] and applies to many kinds of three-axis sensors like gyroscopes and accelerometers [2,13]. The purpose of magnetometer calibration is to estimate the parameters S and h in the model (1).…”

“…A good initial estimate can be derived from (5), as given in [9] or [13,14]. The minimum objective at the true estimate should be close to zero, so it is reasonable to consider   …”

“…These methods exploit the fact that the magnitude of magnetometer measurements is constant regardless of the orientation at the local position. The idea has also been applied to calibrate inertial sensors like accelerometers and gyroscopes [6,9,[12][13][14][15]. The constant magnitude relationship is usually employed to estimate the calibration parameters in the form of the maximum likelihood (ML) estimation problem.…”

An Optimal Calibration Method for a MEMS Inertial Measurement Unit

“…The least squares method is the algorithm most commonly used in scalar calibration to estimate the calibration parameters [6,[11][12][13][14] . H.L Zhang et al [15] implemented an optimal calibration scheme by maximizing the sensitivity of the measurement norms with respect to the calibration parameters. The algorithms typically lead to a biased estimate of the calibration parameters and may give non-optimal estimates of the calibration coefficients.…”