Low-Cost Inertial Measurement Unit Calibration With Nonlinear Scale Factors

Abstract

Inertial measurement units (IMU) have been wildly used to provide accurate location and movement measurement solutions, along with the advances of modern manufacturing technologies. The scale factors of accelerometers and gyroscopes are linear when the range of the sensors are reasonably small, but the factor becomes non-linear when the range gets much bigger. Based on this observation, this paper presents a calibration method for low-cost IMU, by effectively deriving the nonlinear scale factors of the sensors. Two motion patterns of the sensor on a rigid object are moved to collect data for calibration, one motion pattern is to upcast and rotation the rigid object, another pattern is to place the rigid object on a stable base in different attitudes. The rotation motion produces centripetal and Coriolis force, which increases the measurement range of accelerometers. Four cost functions with different weight factors and two sets of data are utilized to optimize the IMU parameters. The weight factor comes from derived formula with input values which are the variance of the noise of the sampled data. The proposed approach was validated and evaluated on both synthetic and real-world data sets, and the experimental results demonstrated the superiority of the proposed approach in improving the accuracy of IMU for long range use. In particular, the errors of acceleration and angular velocity led by our algorithm are significantly smaller than those resulted from the existing approaches using the same testing datasets, demonstrating a remarkable improvement of 64.12% and 47.90%, respectively.

MEMS Inertial Sensor Calibration Technology: Current Status and Future Trends

“…Note that the zero bias of the triaxial accelerometer and gyroscope is b = b x , b y , b z T . The zero-bias errors of both can be expressed as Equation (1).…”

“…As a crucial part of MEMS technology, inertial sensors have been widely used to provide accurate position and motion measurement solutions [1] in many core areas such as aerospace, underwater exploration, robotics, healthcare, and portable devices (such as smartphones, computers, cameras, wearables, pedometers, etc.) [2][3][4][5][6][7][8][9].…”

Turntable IMU Calibration Algorithm Based on the Fourier Transform Technique

“…Having in mind the argument above, we think that using some turntable for calibration, preferably the simplest one, is advisable. In a recent paper [ 16 ], a thorough procedure to calibrate a low-cost IMU on a rotation bench is proposed, with excellent experimental verification. The procedure allows to estimate not just linear, but also a nonlinear calibration model.…”

Relative navigation of UAV swarm in a GPS-denied environment

“…While there are various methods for swarm UAV navigation in GPS-denied environments, our proposed method of using an EKF to fuse range measurements generated by a ranging sensor and an IMU offers several advantages over other methods. Inertial-based methods, for instance, suffer from drift errors and require constant calibration [7]. The use of UWB-based techniques is constrained solely to indoor applications, resulting in subpar precision and a restricted coverage area for outdoor applications, as stated in reference [6].…”