Inertial navigation system

About: Inertial navigation system is a research topic. Over the lifetime, 14582 publications have been published within this topic receiving 190618 citations. The topic is also known as: intertial guidance system & inertial reference platform.

Navigation system for spinning projectiles

Abstract: A navigation system for spinning projectiles using a magnetic spin sensor to measure the projectile roll angle by sensing changes in magnetic flux as the projectile rotates through the earth's magnetic field is disclosed. The magnetic spin sensor measurements are used to despin a body reference frame such that position, velocity, and attitude of the projectile can be determined by using a strapdown inertial navigation system (INS) algorithm. More particularly, a multisensor concept is used to measure pitch and yaw angular rates, by measuring Coriolis acceleration along the roll axis and demodulating the pitch and yaw rates therefrom.

Inertial Navigation Sensors

Abstract: : For many navigation applications, improved accuracy/performance is not necessarily the most important issue, but meeting performance at reduced cost and size is In particular, small navigation sensor size allows the introduction of guidance, navigation, and control into applications previously considered out of reach (eg, artillery shells, guided bullets) Three major technologies have enabled advances in military and commercial capabilities: Ring Laser Gyros, Fiber Optic Gyros, and Micro-Electro-Mechanical Systems (MEMS) gyros and accelerometers RLGs and FOGs are now mature technologies, although there are still technology advances underway for FOGs MEMS is still a very active development area Technology developments in these fields are described with specific emphasis on MEMS sensor design and performance Some aspects of performance drivers are mentioned as they relate to specific sensors Finally, predictions are made of the future applications of the various sensor technologies

Flight tests of attitude determination using gps compared against an inertial navigation unit.

Abstract: Attitude determination using GPS carrier phase has been applied successfully to aircraft in experiments by a number of researchers. In an effort to formally characterize its accuracy and bandwidth performance, a GPS attitude determination system was flight tested against an inertial navigation unit (INU). Based on completely separate physical principles, this testing provides an independent means of evaluating overall performance. For the flight experiments, a twin-engine turboprop transport aircraft was outfitted with a specially designed attitude determination receiver. A strapdown ring laser gyro INU was operated in the main cabin as the independent reference. For system evaluation, a number of test maneuvers were executed, including pitch angles to ± 30 deg and bank angles to ± 60 deg. Performance in moderate turbulence was measured. The impact of structural flexure during aircraft maneuvering was evaluated.

Modern inertial navigation technology and its application

Abstract: Inertial navigation technology is used widely for the guidance of aircraft, ships and land vehicles, as well as in an increasing number of civil applications such as robotics, surveying underground well bores and the control of drilling operations. This article describes the techniques and the sensors used in modern systems and outlines a number of applications in which inertial system technology is being used today.

High-fidelity sensor modeling and self-calibration in vision-aided inertial navigation

Abstract: In this paper, we propose a high-precision pose estimation algorithm for systems equipped with low-cost inertial sensors and rolling-shutter cameras. The key characteristic of the proposed method is that it performs online self-calibration of the camera and the IMU, using detailed models for both sensors and for their relative configuration. Specifically, the estimated parameters include the camera intrinsics (focal length, principal point, and lens distortion), the readout time of the rolling-shutter sensor, the IMU’s biases, scale factors, axis misalignment, and g-sensitivity, the spatial configuration between the camera and IMU, as well as the time offset between the timestamps of the camera and IMU. An additional contribution of this work is a novel method for processing the measurements of the rolling-shutter camera, which employs an approximate representation of the estimation errors, instead of the state itself. We demonstrate, in both simulation tests and real-world experiments, that the proposed approach is able to accurately calibrate all the considered parameters in real time, and leads to significantly improved estimation precision compared to existing approaches.