Inertial reference unit

About: Inertial reference unit is a research topic. Over the lifetime, 1306 publications have been published within this topic receiving 22068 citations. The topic is also known as: IRU.

Heading confidence interval estimation

Abstract: An inertial measurement system is disclosed. The inertial measurement system has an accelerometer processing unit that generates a calibrated accelerometer data. The inertial measurement system further includes a magnetometer processing unit generates a calibrated magnetometer data, and a gyroscope processing unit generates a calibrated gyroscope data. Using the calibrated accelerometer data, the calibrated magnetometer data, and the calibrated gyroscope data, the inertial measurement system generates a heading angle error indicative of the accuracy of the heading angle error.

System for surveying fluid transmission pipelines and the like

Abstract: A pipeline survey pig including an onboard iner­ tial reference unit and signal processing units for receiving acceleration and angular velocity signals generated by the inertial reference unit, calculating resultant values of angular velocity and accelerations and averaging the calculated values to provide record­ able signals related to the position of the pig and changes in curvature of the pipe. The pig is supported by a plurality of resilient cup shape support members which have a stiffness characteristic whereby the natural frequency of vibration which may cause lateral excursions of the pig is less than the signal generat­ ing rate yet greater than the frequency of the signal to be measured. The center of stiffness and the center of gravity of the pig are disposed along the central axis of the pig and the pipeline section being measured and are preferably coincident with each other. The inertial reference unit includes three accelerometers and three gyroscopes oriented orthogonally and may have their axes oriented to intersect at the center of gravity and center of stiffness.

Development of a high-precision calibration method for inertial measurement unit

Abstract: MEMS (Micro-Electromechanical Systems) based IMU (Inertial Measurement Unit) including accelerometers and gyroscopes is widely used for various applications such as INS (Inertial Navigation System), pose estimation devices and others for many industries such as toy, medical, automotive and military industry But MEMS sensor chip originally has bias and sensitivity errors from manufacturing, and there is also axis misalignment when mounting a MEMS chip on IMU PCB layer These error factors cause inaccuracy measurement results and non-linear measurement characteristics of IMU In this paper, accelerometers and gyroscopes are mathematically modeled based on these error factors including bias, sensitivity, coning angle and azimuth angle Calibration procedures for accelerometers and gyroscopes are formulated using nonlinear Gauss-Newton regression logic The effectiveness of the proposed calibration procedures are proven by simulation and experiment using high accuracy 2-axis rotational gimbal motion system

Microelectromechnical Systems Inertial Measurement Unit Error Modelling and Error Analysis for Low-cost Strapdown Inertial Navigation System

Abstract: This paper presents error modelling and error analysis of microelectromechnical systems (MEMS) inertial measurement unit (IMU) for a low-cost strapdown inertial navigation system (INS). The INS consists of IMU and navigation processor. The IMU provides acceleration and angular rate of the vehicle in all the three axes. In this paper, errors that affect the MEMS IMU, which is of low cost and less volume, are stochastically modelled and analysed using Allan variance. Wavelet decomposition has been introduced to remove the high frequency noise that affects the sensors to obtain the original values of angular rates and accelerations with less noise. This increases the accuracy of the strapdown INS. The results show the effect of errors in the output of sensors, easy interpretation of random errors by Allan variance, the increase in the accuracy when wavelet decomposition is used for denoising inertial sensor raw data. Defence Science Journal, 2009, 59(6), pp.650-658 , DOI:http://dx.doi.org/10.14429/dsj.59.1571