Topic
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.
Papers published on a yearly basis
Papers
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TL;DR: In this article, the role of integrated optics and photonic integrated circuit technology in the enhancement of gyroscope performance and compactness is broadly discussed, and the architecture of new slow-light integrated angular rate sensors is described.
Abstract: Photonics for angular rate sensing is a well-established research field having very
important industrial applications, especially in the field of strapdown inertial
navigation. Recent advances in this research field are reviewed. Results obtained in
the past years in the development of the ring laser gyroscope and the fiber optic
gyroscope are presented. The role of integrated optics and photonic integrated
circuit technology in the enhancement of gyroscope performance and compactness is
broadly discussed. Architectures of new slow-light integrated angular rate sensors
are described. Finally, photonic gyroscopes are compared with other solid-state
gyros, showing their strengths and weaknesses.
200 citations
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TL;DR: A 3D perception system based on voxel-grid model for static and moving obstacles detection using discriminative analysis and ego-motion information and a complete framework for ground surface estimation and static/moving obstacle detection in driving environments is proposed.
197 citations
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TL;DR: In this paper, a meteorological mini unmanned aerial vehicle (M2AV) was used for measuring the meteorological wind, which is the vector difference between the aircraft speed relative to the earth (inertial velocity) and the airflow (true airspeed) computed from five-hole-probe pressure measurements in combination with calibration coefficients obtained during wind tunnel calibration.
Abstract: The meteorological mini unmanned aerial vehicle (M2AV) was used for measuring the meteorological wind. The wind is the vector difference between the aircraft speed relative to the earth (inertial velocity) and relative to the airflow (true airspeed). The latter was computed from five-hole-probe pressure measurements in combination with calibration–coefficient polynomials obtained during wind tunnel calibration. The aircraft inertial velocity, position, and attitude were calculated using a Kalman filter that combined data from a global positioning system (GPS) and an inertial navigation system (INS). The temporal (and spatial) resolution of the M2AV wind measurement is remarkably fine. An inertial subrange of locally isotropic turbulence can be measured up to 40 Hz (or 0.55 m at 22 m s−1 airspeed). The first M2AV wind estimation showed some systematic deviations compared to the expected values (like a constant mean wind in every flight direction). Therefore, an in-flight wind calibration technique...
197 citations
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29 Nov 1988
TL;DR: An efficient, federated Kalman filtering method is presented, based on rigorous information-sharing principles, that applies to decentralized navigation systems in which one or more sensor-dedicated local filters feed a larger master filter.
Abstract: An efficient, federated Kalman filtering method is presented, based on rigorous information-sharing principles. The method applies to decentralized navigation systems in which one or more sensor-dedicated local filters feed a larger master filter. The local filters operate in parallel, processing unique data from their local sensors, and common data from a shared inertial navigation system. The master filter combines local filter outputs at a selectable reduced rate, and yields estimates that are globally optimal or subset-optimal. The method provides major improvements in throughput (speed) and fault tolerance, and is well suited to real-time implementation. Practical federated filter examples are presented, and discussed in terms of structure, accuracy, fault tolerance, throughput, data compression, and other real-time issues. >
197 citations
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01 Mar 2008TL;DR: A vision based navigation system which combines inertial sensors, visual odometer and registration of a UAV on-board video to a given geo-referenced aerial image has been developed and tested on real flight-test data and shows that it is possible to extract useful position information from aerial imagery even when the UAV is flying at low altitude.
Abstract: The aim of this paper is to explore the possibility of using geo-referenced satellite or aerial images to augment an Unmanned Aerial Vehicle (UAV) navigation system in case of GPS failure. A vision based navigation system which combines inertial sensors, visual odometer and registration of a UAV on-board video to a given geo-referenced aerial image has been developed and tested on real flight-test data. The experimental results show that it is possible to extract useful position information from aerial imagery even when the UAV is flying at low altitude. It is shown that such information can be used in an automated way to compensate the drift of the UAV state estimation which occurs when only inertial sensors and visual odometer are used.
196 citations