PROJECT TITLE :

Calibration of low-cost triaxial inertial sensors

ABSTRACT:

Accelerometers (ACCs) and gyroscopes (gyros) are commonly called inertial sensors and their orthogonal triads generally form an inertial measurement unit (IMU) used as a core means of a navigation system. Before the navigation system is to be used, it is necessary to perform its calibration. A typical method of the IMU calibration usually estimates scale-factors, orthogonality or misalignment errors, and offsets of both triads. These parameters compose the thus-known as sensor error model (SEM). The process of obtaining correct data that describes the motion performed at intervals the calibration usually requires a pricey and specialised means [1], [two]. Thus, a lot of effort has been put into cost-effective calibration using an optical motion tracking system [three]–[half dozen], or transferring the calibration into a state estimation downside [seven]. In the ACC case, most of the current calibration strategies utilize the fact that ACCs are full of gravity when they are beneath static conditions. Thus, we have a tendency to proceed with calibration performed underneath static conditions, that utilizes the information of the gravity magnitude and ACC output measurements collected at predetermined orientations and performs ACC SEM estimation using nonlinear optimization [half dozen], [eight]–[ten]. Within the gyro case, calibration primarily based on the Earth's rate may be inapplicable, for example because of the actual fact that Earth's rate is underneath or around the resolution of the gyro, and so other means that to apply and measure angular rates need to be used. This example commonly arises in the case of low-price MEMS (Micro-Electro-Mechanical System) based mostly gyros. Thus, expensive mechanical platforms are typically inevitable [11]–[14].