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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.


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Journal ArticleDOI
15 Aug 2013-Sensors
TL;DR: The proposed method is described and applied in a real-time integrated system with two integration strategies, namely, loosely coupled and tightly coupled schemes, respectively, and aims to avoid the multipath problem.
Abstract: The integration of an Inertial Navigation System (INS) and the Global Positioning System (GPS) is common in mobile mapping and navigation applications to seamlessly determine the position, velocity, and orientation of the mobile platform. In most INS/GPS integrated architectures, the GPS is considered to be an accurate reference with which to correct for the systematic errors of the inertial sensors, which are composed of biases, scale factors and drift. However, the GPS receiver may produce abnormal pseudo-range errors mainly caused by ionospheric delay, tropospheric delay and the multipath effect. These errors degrade the overall position accuracy of an integrated system that uses conventional INS/GPS integration strategies such as loosely coupled (LC) and tightly coupled (TC) schemes. Conventional tightly coupled INS/GPS integration schemes apply the Klobuchar model and the Hopfield model to reduce pseudo-range delays caused by ionospheric delay and tropospheric delay, respectively, but do not address the multipath problem. However, the multipath effect (from reflected GPS signals) affects the position error far more significantly in a consumer-grade GPS receiver than in an expensive, geodetic-grade GPS receiver. To avoid this problem, a new integrated INS/GPS architecture is proposed. The proposed method is described and applied in a real-time integrated system with two integration strategies, namely, loosely coupled and tightly coupled schemes, respectively. To verify the effectiveness of the proposed method, field tests with various scenarios are conducted and the results are compared with a reliable reference system.

93 citations

Book ChapterDOI
01 Jan 2013
TL;DR: This paper proposes an Observability-Constrained VINS (OC-VINS) methodology that explicitly adheres to the observability properties of the true system, and applies this approach to the Multi-State Constraint Kalman Filter (MSC-KF).
Abstract: In this paper, we study estimator inconsistency in Vision-aided Inertial Navigation Systems (VINS). We show that standard (linearized) estimation approaches, such as the Extended Kalman Filter (EKF), can fundamentally alter the system observability properties, in terms of the number and structure of the unobservable directions. This in turn allows the influx of spurious information, leading to inconsistency. To address this issue, we propose an Observability-Constrained VINS (OC-VINS) methodology that explicitly adheres to the observability properties of the true system.We apply our approach to the Multi-State Constraint Kalman Filter (MSC-KF), and provide both simulation and experimental validation of the effectiveness of our method for improving estimator consistency.

93 citations

Journal ArticleDOI
16 Oct 2015-Sensors
TL;DR: A newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented.
Abstract: In this paper, a newly-developed direct georeferencing system for the guidance, navigation and control of lightweight unmanned aerial vehicles (UAVs), having a weight limit of 5 kg and a size limit of 1.5 m, and for UAV-based surveying and remote sensing applications is presented. The system is intended to provide highly accurate positions and attitudes (better than 5 cm and 0.5°) in real time, using lightweight components. The main focus of this paper is on the attitude determination with the system. This attitude determination is based on an onboard single-frequency GPS baseline, MEMS (micro-electro-mechanical systems) inertial sensor readings, magnetic field observations and a 3D position measurement. All of this information is integrated in a sixteen-state error space Kalman filter. Special attention in the algorithm development is paid to the carrier phase ambiguity resolution of the single-frequency GPS baseline observations. We aim at a reliable and instantaneous ambiguity resolution, since the system is used in urban areas, where frequent losses of the GPS signal lock occur and the GPS measurement conditions are challenging. Flight tests and a comparison to a navigation-grade inertial navigation system illustrate the performance of the developed system in dynamic situations. Evaluations show that the accuracies of the system are 0.05° for the roll and the pitch angle and 0.2° for the yaw angle. The ambiguities of the single-frequency GPS baseline can be resolved instantaneously in more than 90% of the cases.

93 citations

Proceedings ArticleDOI
16 Feb 1994
TL;DR: Drawbacks of classical electromagnetic servo-accelerometers are overcome by using a bulk micromachined capacitive accelerometer and a CMOS interface circuit.
Abstract: Precision accelerometers for applications such as inertial navigation and guidance, tilt measurement and low-level vibration monitoring can be characterized by shown specifications . Drawbacks of classical electromagnetic servo-accelerometers (fabrication cost, power consumption and shock resistance) are overcome by using a bulk micromachined capacitive accelerometer and a CMOS interface circuit. >

93 citations

Journal ArticleDOI
TL;DR: NavLab has been used extensively for mass-production of accurate navigation results (having post-processed more than 5000 hours of real data in four continents).
Abstract: The ambition of getting one common tool for a great variety of navigation tasks was the background for the development of NavLab (Navigation Laboratory). The main emphasis during the development has been a solid theoretical foundation with a stringent mathematical representation to ensure that statistical optimality is maintained throughout the entire system. NavLab is implemented in Matlab, and consists of a simulator and an estimator. ○ Simulations are carried out by specifying a trajectory for the vehicle, and the available types of sensors. The output is a set of simulated sensor measurements. ○ The estimator is a flexible aided inertial navigation system, which makes optimal Kalman filtered and smoothed estimates of position, attitude and velocity based on the available set of measurements. The measurements can be either from the simulator or from real sensors of a vehicle. This structure makes NavLab useful for a wide range of navigation applications, including research and development, analysis, real data post-processing and as a decision basis for sensor purchase and mission planning. NavLab has been used extensively for mass-production of accurate navigation results (having post-processed more than 5000 hours of real data in four continents). Vehicles navigated by NavLab include autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs), ships and aircraft.

93 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023309
2022657
2021491
2020889
20191,003
20181,013