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.

Inertial system for measurement of the dynamic response and status of the vehicle suspension elements

Abstract: The current paper describes the information and communication system, based on micromechanical inertial sensors (MEMS) to measure the dynamic response and status of the vehicle suspension elements. It consists of an inertial sensor network from at least two sensors, which are situated on the moving elements of the vehicle suspension. The communication system part reads and stores the inertial sensor data while the information system part calculates the frequency response, attenuation time, resonance frequencies and distance between moving parts. The calculated distance is compared with the adjusted clearance and the system accuracy is shown. It is shown that the system is capable to measure the distances from 0.6 to 1.0mm with 0.1mm accuracy. The inertial data scanning is performed with a sampling frequency of 160Hz, according to the expected peak accelerations and translations.

Constrained non-linear fitting for stochastic modeling of inertial sensors

Abstract: Nowadays with the development of inertial sensors based on Micro-Electromechanical Systems (MEMS), embedded accelerometers and gyroscopes can be found in several devices and platforms ranging from watches, smart phones, video game consoles up to terrestrial navigation and unmanned aerial vehicles (UAVs), etc. Despite the wide range of applications where such sensors are being used, it is well known that low-cost inertial sensors (MEMS grade) are affected by stochastic and deterministic errors that degrade the systems performance in a short period of time, which compromise the integrity and reliability, specially in navigation systems. Although different researches have been achieved to model the stochastic error of the MEMS sensors, it should be mentioned that the estimation of the stochastic noise component is still a non-trivial task. Therefore in this paper we evaluate an approach to obtain the stochastic error parameters by using a constrained non-linear fitting. We also implemented some of the most relevant works reported in the literature for estimating the stochastic error parameters of MEMS sensors. In order to evaluate the performance, a simulation analysis is achieved by generating a noise sources that typically influence the inertial sensors. The simulation shows that the non-linear fitting provides better results than traditional and some recent techniques in terms of the estimation of noise sources parameters. Eventually, we applied it to estimate the stochastic error model parameters from two MEMS-based Inertial Measurement Units (IMUs), specifically, the low-cost Microstrain 3DM-GX3-IMU and the ultra-low-cost Sparkfun Atomic IMU 6 dof. The stochastic error model parameters obtained from the analysis can be easily adapted into a GPS/INS integrated system.

In-flight estimation of gyro noise on the Upper Atmosphere Research Satellite (UARS) and Extreme Ultraviolet Explorer (EUVE) missions

Abstract: This paper characterizes the low-frequency noise response of the Teledyne dry rotor inertial reference unit (DRIRU) gyroscopes on the Upper Atmosphere Research Satellite (UARS) and the Extreme Ultraviolet Explorer (EUVE). The accuracy of spacecraft attitude estimation algorithms that use gyro data for propagating the spacecraft attitude is sensitive to gyro noise. EUVE gyro data were processed to validate a single-axis gyro noise model, which is used onboard various spacecraft. The paper addresses the potential impact of temperature effects on the gyro noise model and the overall impact on attitude determination accuracy. The power spectral density (PSD) of the gyro noise is estimated from UARS in-flight data by Fast Fourier Transform (FFT). The role of actuator dynamics on the PSD function is also discussed.

Research on integrated alignment of rotary strapdown inertial navigation system

Abstract: The initial alignment accuracy of strapdown inertial navigation system (SINS) is limited by the gyro drift and accelerometer bias, and the integrated alignment is generally used to diminish the error of initial alignment. In this paper, a reasonable dual-axis rotation scheme is designed to improve the observability degree of rotary strapdown inertial navigation system, and a novel integrated alignment method with external velocity and attitude information is proposed based on the previous method with velocity information. Simulation results show that the estimation speed of platform misalignment angles (primary reflects on heading misalignment angle) in the novel method is faster than in the previous method, and the estimation accuracy is much higher. The new scheme should be the preferred one if conditions permit.

Method of functional control of an inertial platform of a moving craft

Abstract: A method for verifying an inertial unit for a moving body, the unit being mounted on a movement simulator, and the method includes: theoretical modeling of the inertial unit on the movement simulator, supplying theoretical inertial data representing measurement inertial data deemed to be measured by the inertial unit; simulation modeling including modeling of the inertial unit in a real navigation environment, the simulation modeling being fed with control commands and supplying simulation inertial data representing output data from the inertial unit in real navigation environment; calculating control commands as a function of the measurement inertial data, the simulation inertial data, and the theoretical inertial data; and validating the inertial unit by comparing the path of the moving body with a reference path.