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.

Precision attitude determination for multimission spacecraft

Abstract: Attitude determination algorithms for a multimission spacecraft are derived and their performance analyzed. The attitude determination system is composed of a strapdown Inertial Reference Unit (IRU), two fixed head star trackers, and an onboard computer. IRU data is processed to maintain real-time knowledge of spacecraft attitude relative to an inertial reference frame. Star tracker data is processed using Kalman filtering techniques to estimate and correct the attitude determination errors and the gyro drift compensation errors. The results of a star availability analysis for stellar, solar and earth pointing missions are presented. Linear covariance analysis techniques are used to evaluate nominal attitude determination performance, the effects of sensor measurement accuracy variations, the effects of errors in knowledge of sensor measurement accuracy, and the effects of star tracker misalignment errors. Results of a nonlinear simulation analysis of attitude determination performance are also presented. These analyses show that precision attitude determination for stellar, solar and earth pointing missions is achieved.

Invariant observers for attitude and heading estimation from low-cost inertial and magnetic sensors

Abstract: In this paper we propose invariant nonlinear observers for attitude and heading estimation using directly the measurements from low-cost inertial and magnetic sensors. In particular we propose a simple and easy-to-tune observer where moreover the estimated attitude behaves well even in the presence of magnetic disturbances.

An enhanced multi-position calibration method for consumer-grade inertial measurement units applied and tested

Abstract: An accurate inertial measurement unit (IMU) is a necessity when considering an inertial navigation system capable of giving reliable position and velocity estimates even for a short period of time. However, even a set of ideal gyroscopes and accelerometers does not imply an ideal IMU if its exact mechanical characteristics (i.e. alignment and position information of each sensor) are not known. In this paper, the standard multi-position calibration method for consumer-grade IMUs using a rate table is enhanced to exploit also the centripetal accelerations caused by the rotation of the table. Thus, the total number of measurements rises, making the method less sensitive to errors and allowing use of more accurate error models. As a result, the accuracy is significantly enhanced, while the required numerical methods are simple and efficient. The proposed method is tested with several IMUs and compared to existing calibration methods.

Enhanced MEMS-IMU/odometer/GPS integration using mixture particle filter

Abstract: Dead reckoning techniques such as inertial navigation and odometry are integrated with GPS to avoid interruption of navigation solutions due to lack of visible satellites. A common method to achieve a low-cost navigation solution for land vehicles is to use a MEMS-based inertial measurement unit (IMU) for integration with GPS. This integration is traditionally accomplished by means of a Kalman filter (KF). Due to the significant inherent errors of MEMS inertial sensors and their time-varying changes, which are difficult to model, severe position error growth happens during GPS outages. The positional accuracy provided by the KF is limited by its linearized models. A Particle filter (PF), being a nonlinear technique, can accommodate for arbitrary inertial sensor characteristics and motion dynamics. An enhanced version of the PF, called Mixture PF, is employed in this paper. It samples from both the prior importance density and the observation likelihood, leading to an improved performance. Furthermore, in order to enhance the performance of MEMS-based IMU/GPS integration during GPS outages, the use of pitch and roll calculated from the longitudinal and transversal accelerometers together with the odometer data as a measurement update is proposed in this paper. These updates aid the IMU and limit the positional error growth caused by two horizontal gyroscopes, which are a major source of error during GPS outages. The performance of the proposed method is examined on road trajectories, and results are compared to the three different KF-based solutions. The proposed Mixture PF with velocity, pitch, and roll updates outperformed all the other solutions and exhibited an average improvement of approximately 64% over KF with the same updates, about 85% over KF with velocity updates only, and around 95% over KF without any updates during GPS outages.

Head tracking relative to a moving vehicle or simulator platform using differential inertial sensors

Abstract: Inertial trackers have been successfully applied to a wide range of HMD applications including virtual environment training, VR gaining and even fixed-base vehicle simulation, in which they have gained widespread acceptance due to their superior resolution and low latency. Until now, it has been impossible to use inertial trackers in applications which require tracking motion relative to a moving platform, such as motion-base simulators, virtual environment trainers deployed on board ships, and live vehicular applications including helmet-mounted cueing systems and enhanced vision or situational awareness displays. This paper describes a new technique which makes it possible to use inertial head- tracking systems on-board moving platforms by computing the motion of a `tracking' Inertial Measurement Unit (IMU) mounted on the HMD relative to a `reference' IMU rigidly attached to the moving platform. Detailed kinematic equations are derived, and simulation results are provided for the particular case of an inertial tracker with drift correction by means of ultrasonic ranging sensors, but the conclusions can be applied to hybrid inertial trackers involving optical, magnetic, or RF drift correction as well.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.