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.

The combination of inertial navigation and radio aids

Abstract: By measuring forces and moments that constrain a body of known inertial characteristics to move with a vehicle it is possible to determine acceleration in a set of specified axes and hence change in velocity and position. The principles of this method of navigation, known as inertial navigation, are outlined, and it is shown that the many possibilities of a practical realization can all be expressed in terms of a single block schematic of a computer which corrects for the expected variations in the specific force of gravity as a function of position and time.The magnitude of the problem of designing suitable gyroscopes and accelerometers is discussed, and the effect is calculated of certain errors in the components. Means for combining inertial navigation with radio navigation aids are outlined, and it is shown that these give an effective memory over periods in which the radio aid may be inoperative, a heavy filtering of the radio-aid output without introducing lag and loss of information, and interpolation between outputs of a low-data-rate system. The performance requirements for gyroscopes and accelerometers to obtain this can be much less stringent than for pure inertial navigation.

Requirements for gyroscopes for inertial navigation

Abstract: A simple explanation of inertial navigation is presented. The difference between `gimballed? and `strapdown? systems is explained. The performance requirements of a gyro for one nautical mile per hour aircraft IN system are derived.

The Research of Motion Capture Technology Based on Inertial Measurement

Abstract: The motion capture technologies have been widely used in the following areas: human movement science, human-computer interaction and control, medical analysis, film, game production, and etc. This paper presented a motion capture system based on inertial sensors. The system is mainly composed of the inertial sensor unit and real-time monitoring unit on PC. Meanwhile, Sensor units exchange data with PC through BSN (body sensor network). One sensor measurement unit contains a three-axis gyroscope, a three-axis accelerometer, a three-axis magnetometer and a network communication unit. The inertial sensor units are installed on the different parts of body. In the system, the inertial sensor data are collected, and then adaptive Kalman Filter algorithm is used to estimate the body gesture. The Experiments show that this way have some advantages such as: high precision, dynamic, and almost no drift. Furthermore, the data can be changed smoothly.