Multisensor Integration Methods in the Development of a Fault-Tolerant Train Navigation System

2003 ◽  
Vol 56 (3) ◽  
pp. 385-398 ◽  
Author(s):  
Ahmad Mirabadi ◽  
Felix Schmid ◽  
Neil Mort
Keyword(s):  
Navigation System ◽  
Doppler Radar ◽  
Fault Tolerant ◽  
Critical Role ◽  
Fault Detection And Isolation ◽  
Sensor Data ◽  
Estimation Methods ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Train Positioning

Onboard train positioning (navigation) plays a vital and safety critical role in advanced Automatic Train Control (ATC) and Automatic Train Protection (ATP) systems. Such onboard systems are also essential for moving block signalling and control systems for railways. The application of multi-sensor fusion algorithms to the vehicle navigation field has made it possible to create inexpensive and accurate positioning systems, which will satisfy the railways' requirements. The state estimation methods involved in Kalman filtering have proved to be some of the most effective techniques in multi-sensor data fusion. A multi-sensor navigation system is introduced in this paper to address the shortcomings of the existing train positioning systems. The proposed system utilizes the Global Positioning System (GPS), Doppler radar, gyroscopes, tachometers, digital maps and balises. In order to provide fault detection and isolation capabilities, a hierarchical structure is proposed for the multi-sensor integration system in which different combinations of navigation systems would function. Several data integration nodes, including DR/GPS, DR/Balise, and DR/GPS/Balise, are studied in more detail and their performances are evaluated.

Navigation Based on Sensors in Smartphones

2018 ◽  
pp. 368-396
Author(s):  
Guenther Retscher ◽  
Allison Kealy
Keyword(s):  
Navigation System ◽  
Inertial Navigation ◽  
Dead Reckoning ◽  
Activity Monitoring ◽  
Navigation Systems ◽  
Location Tracking ◽  
Map Matching ◽  
Complex Environments ◽  
Positioning Systems ◽  
Cooperative Positioning

With the increasing ubiquity of smartphones and tablets, users are now routinely carrying a variety of sensors with them wherever they go. These devices are enabling technologies for ubiquitous computing, facilitating continuous updates of a user's context. They have built-in MEMS-based accelerometers for ubiquitous activity monitoring and there is a growing interest in how to use these together with gyroscopes and magnetometers to build dead reckoning (DR) systems for location tracking. Navigation in complex environments is needed mainly by consumer users, private vehicles, and pedestrians. Therefore, the navigation system has to be small, easy to use, and have reasonably low levels of power consumption and price. The technologies and techniques discussed here include the fusion of inertial navigation (IN) and other sensors, positioning based on signals from wireless networks (such as Wi-Fi), image-based methods, cooperative positioning systems, and map matching (MM). The state-of-the-art of MEMS-based location sensors and their integration into modern navigation systems are also presented.

A Review of Multisensor Fusion Methodologies for Aircraft Navigation Systems

2005 ◽  
Vol 58 (3) ◽  
pp. 405-417 ◽  
Author(s):  
David J. Allerton ◽  
Huamin Jia
Keyword(s):  
Kalman Filter ◽  
Data Fusion ◽  
Navigation System ◽  
Review Paper ◽  
Fault Tolerant ◽  
Navigation Systems ◽  
System Architectures ◽  
Advantages And Disadvantages ◽  
Aircraft Navigation ◽  
Fusion Methods

This paper reviews currently existing fault-tolerant navigation system architectures and data fusion methods used in the design and development of integrated aircraft navigation systems and also compares their advantages and disadvantages. Four fault-tolerant navigation system architectures are reviewed and the associated Kalman filter architectures and algorithms are discussed. These techniques have been used in most integrated aircraft navigation systems. The aim of this review paper is to provide a guide for navigation system designers to develop future aircraft multisensor navigation systems.

scholarly journals Selected qualities of mobile maps for indoor navigation

2019 ◽  
Vol 51 (4) ◽  
pp. 155-165
Author(s):  
Dariusz Gotlib
Keyword(s):  
Navigation System ◽  
Data Model ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Stages Of Development ◽  
Positioning Systems ◽  
Presentation Method ◽  
Dynamic Growth ◽  
Definition Of ◽  
Mobile Maps

Abstract The map is the key element in any navigation system. The dynamic growth of indoor navigation systems requires improvements in quality not only of positioning systems but also of maps of building interiors. Most emergent solutions in this field do not use cartographic knowledge. Cartographic methodology for representing building interiors is still in its initial stages of development. Its proper use may, however, be of great importance to the effectiveness of indoor navigation. The author presents important features that indoor mobile maps should possess, for both the data model and the presentation method to be used. In this context, the question of the contemporary definition of a map is also discussed.

Integrated Navigation Systems for Aircraft

1983 ◽  
Vol 36 (3) ◽  
pp. 359-378
Author(s):  
R. F. Stokes ◽  
S. G. Smith
Keyword(s):  
Navigation System ◽  
Digital Computer ◽  
Reference System ◽  
Doppler Radar ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Major Objective ◽  
Southern England ◽  
Return Home ◽  
Operational Concept

Work on integrated navigation for aircraft started at RAF Farnborough at least as early as the mid 1950s. At that time the Inertial Navigator (IN) for a guided bomb was being developed and the navigation of the aircraft to the target used a combination of the weapon IN, Doppler radar and position fixing. An output of the navigation process was a calibration of the weapon IN. The operational concept was interesting in that after weapon release the aircraft had to return home using Doppler and compass.Development of this system included flight trials in raf and a & aee aircraft using the Decca Navigator chains in Southern England for position reference. The same method was used in the development of the FSP 100 IN intended for the TSR 2 which took place in 1960/63. On these trials an early airborne digital computer on board the trials aircraft enabled Decca, Doppler and the IN information to be recorded and processed in-flight in a form suitable for post-flight analysis using a ground digital computer. This technique formed the basis for producing the reference navigation system which has been used for all our subsequent trials. The production of a position, velocity and attitude reference system for trials of inertial and other navigation systems has formed a major objective for RAE work on integrated navigation since that time.

scholarly journals Validation of the Accuracy and Convergence Time of Real Time Kinematic Results Using a Single Galileo Navigation System

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2412 ◽  
Author(s):  
Zbigniew Siejka
Keyword(s):  
Real Time ◽  
Navigation System ◽  
Satellite System ◽  
Convergence Time ◽  
Navigation Systems ◽  
Precise Position ◽  
Positioning Systems ◽  
Real Time Kinematic ◽  
Global Navigation

For the last two decades, the American GPS and Russian GLONASS were the basic systems used in global positioning and navigation. In recent years, there has been significant progress in the development of positioning systems. New regional systems have been created, i.e., the Japanese Quasi-Zenith Satellite System (QZSS) and Indian Regional Navigational Satellite System (IRNSS). A plan to build its own regional navigation system named Korean Positioning System (KPS) was announced South Korea on 5 February 2018. Currently, two new global navigation systems are under development: the European Galileo and the Chinese BeiDou. The full operability of both systems by 2020 is planned. The paper deals with a possibility of determination of the user’s position from individual and independent global navigation satellite system (GNSS). The article is a broader concept aimed at independent determination of precise position from individual GPS, GLONASS, BeiDou and Galileo systems. It presents real time positioning results (Real Time Kinematic-RTK) using signals from Galileo satellites only. During the test, 14 Galileo satellites were used and the number of simultaneously observed Galileo satellites varied from five to seven. Real-time measurements were only possible in certain 24-h observation windows. However, their number was completed within 6 days at the end of 2017 and beginning of 2018, so there was possible to infer about the current availability, continuity, convergence time and accuracy of the RTK measurements. In addition, the systematic errors were demonstrated for the Galileo system.

scholarly journals Fault Tolerant Control in Redundant Inertial Navigation System

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaoqiang Dai ◽  
Lin Zhao ◽  
Zhen Shi
Keyword(s):  
Navigation System ◽  
Control Algorithm ◽  
Inertial Navigation System ◽  
Control Method ◽  
Fault Tolerant ◽  
Inertial Navigation ◽  
Fault Tolerant Control ◽  
Fault Detection And Isolation ◽  
Feedback Gain ◽  
Noise Characteristics

Conventional fault detection and isolation technology cannot fully ensure system redundancy features when sensors experience drift in a redundant inertial navigation system. A new fault tolerant control method employs state estimation and state feedback techniques to compensate the sensor drift. However, the method is sensitive to measurement noise characteristics, and the performance of the method nearly depends on the feedback gain. This paper proposes an improved fault tolerant control algorithm, which employs an adaptive extended Kalman particle filter (AEKPF) to deal with unknown noise characteristics and model inaccuracies. In addition, a drift factor is introduced in the improved fault tolerant controlin order to reduce the dependence of compensation system on the feedback gain. Simulation results show that the improved fault tolerant control algorithm can effectively correct the faulty sensor even when the multiple erroneous sensors are producing faulty outputs simultaneously. Meanwhile, the AEKPF is able to solve the problem of unknown non-Gaussian noise characteristics. Moreover, the feedback gain is significantly improved by the drift factor.

Utilisation of Robotic Navigation Systems in the Treatment of Atrial Fibrillation

2010 ◽  
Vol 6 (3) ◽  
pp. 60
Author(s):  
Richard Schilling ◽  
Keyword(s):  
Atrial Fibrillation ◽  
Catheter Ablation ◽  
Navigation System ◽  
Antiarrhythmic Drugs ◽  
Rhythm Control ◽  
Navigation Systems ◽  
Robotic Navigation ◽  
Increased Risk ◽  
Common Strategy ◽  
Catheter Navigation

Atrial fibrillation (AF) is linked to an increased risk of adverse cardiovascular events. While rhythm control with antiarrhythmic drugs (AADs) is a common strategy for managing patients with AF, catheter ablation may be a more efficacious and safer alternative to AADs for sinus rhythm control. Conventional catheter ablation has been associated with challenges during the arrhythmia mapping and ablation stages; however, the introduction of two remote catheter navigation systems (a robotic and a magnetic navigation system) may potentially overcome these challenges. Initial clinical experience with the robotic navigation system suggests that it offers similar procedural times, efficacy and safety to conventional manual ablation. Furthermore, it has been associated with reduced fluoroscopy exposure to the patient and the operator as well as a shorter fluoroscopy time compared with conventional catheter ablation. In the future, the remote navigation systems may become routinely used for complex catheter ablation procedures.

scholarly journals Consistency of the Empirical Distributions of Navigation Positioning System Errors with Theoretical Distributions—Comparative Analysis of the DGPS and EGNOS Systems in the Years 2006 and 2014

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 31
Author(s):  
Mariusz Specht
Keyword(s):  
Normal Distribution ◽  
Root Mean Square ◽  
Statistical Tests ◽  
Position Error ◽  
Positioning System ◽  
Navigation Systems ◽  
Mean Square ◽  
Positioning Systems ◽  
Position Errors ◽  
System Errors

Positioning systems are used to determine position coordinates in navigation (air, land and marine). The accuracy of an object’s position is described by the position error and a statistical analysis can determine its measures, which usually include: Root Mean Square (RMS), twice the Distance Root Mean Square (2DRMS), Circular Error Probable (CEP) and Spherical Probable Error (SEP). It is commonly assumed in navigation that position errors are random and that their distribution are consistent with the normal distribution. This assumption is based on the popularity of the Gauss distribution in science, the simplicity of calculating RMS values for 68% and 95% probabilities, as well as the intuitive perception of randomness in the statistics which this distribution reflects. It should be noted, however, that the necessary conditions for a random variable to be normally distributed include the independence of measurements and identical conditions of their realisation, which is not the case in the iterative method of determining successive positions, the filtration of coordinates or the dependence of the position error on meteorological conditions. In the preface to this publication, examples are provided which indicate that position errors in some navigation systems may not be consistent with the normal distribution. The subsequent section describes basic statistical tests for assessing the fit between the empirical and theoretical distributions (Anderson-Darling, chi-square and Kolmogorov-Smirnov). Next, statistical tests of the position error distributions of very long Differential Global Positioning System (DGPS) and European Geostationary Navigation Overlay Service (EGNOS) campaigns from different years (2006 and 2014) were performed with the number of measurements per session being 900’000 fixes. In addition, the paper discusses selected statistical distributions that fit the empirical measurement results better than the normal distribution. Research has shown that normal distribution is not the optimal statistical distribution to describe position errors of navigation systems. The distributions that describe navigation positioning system errors more accurately include: beta, gamma, logistic and lognormal distributions.

scholarly journals MS-2 Minimally invasive glioma surgery with navigation system and tubular retractor

2020 ◽  
Vol 2 (Supplement_3) ◽  
pp. ii2-ii3
Author(s):  
Kazuhiko Kurozumi
Keyword(s):  
Navigation System ◽  
Diffusion Tensor ◽  
Therapeutic Option ◽  
Normal Brain ◽  
Navigation Systems ◽  
Glioma Surgery ◽  
Tubular Retractor ◽  
Neuronavigation System ◽  
Magnetic Resonance Imaging Mri ◽  
Neurological Surgery

Abstract Navigation systems are reliable and safe for neurological surgery. Navigation is an attractive and innovative therapeutic option. Recently, endo and exoscopic surgeries have been gradually increasing in neurosurgery. We are currently trialing to use 4K and 8K systems to improve the accuracy and safety of our surgical procedures. Surgeries for deep-seated tumors are challenging because of the difficulty in creating a corridor and observing the interface between lesions and the normal area. In total, 315 patients underwent surgery at Okayama University between 2017 and 2019. Among them, we experienced 92 glioma surgeries using navigation systems. Preoperatively, we performed computed tomography imaging and contrast-enhanced magnetic resonance imaging (MRI) for the neuronavigation system. We experienced Curve(TM) Image Guided Surgery (BrainLab, Munich, Germany). The surgical trajectory was planned with functional MRI and diffusion tensor imaging to protect the eloquent area and critical vasculature of the brain. We used a clear plastic tubular retractor system, the ViewSite Brain Access System, for surgery of deep seated gliomas. We gently inserted and placed the ViewSite using the neuronavigation. The tumor was observed and resected through the ViewSite tubular retractor under a microscope and endoscope. If the tumor was large, we switched the ViewSite tubular retractor to brain spatulas to identify the boundary between the normal brain and lesion. We are currently using the combination of the tubular retractor and brain spatulas using navigation system. Here, we present and analyze our preoperative simulation, surgical procedure, and outcomes.

An Improved and Efficient Algorithm for SINS/GPS/Doppler Integrated Navigation Systems

2012 ◽  
Vol 245 ◽  
pp. 323-329 ◽  
Author(s):  
Muhammad Ushaq ◽  
Jian Cheng Fang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensor ◽  
Inertial Navigation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Efficient Manner ◽  
Position Errors

Inertial navigation systems exhibit position errors that tend to grow with time in an unbounded mode. This degradation is due, in part, to errors in the initialization of the inertial measurement unit and inertial sensor imperfections such as accelerometer biases and gyroscope drifts. Mitigation to this growth and bounding the errors is to update the inertial navigation system periodically with external position (and/or velocity, attitude) fixes. The synergistic effect is obtained through external measurements updating the inertial navigation system using Kalman filter algorithm. It is a natural requirement that the inertial data and data from the external aids be combined in an optimal and efficient manner. In this paper an efficient method for integration of Strapdown Inertia Navigation System (SINS), Global Positioning System (GPS) and Doppler radar is presented using a centralized linear Kalman filter by treating vector measurements with uncorrelated errors as scalars. Two main advantages have been obtained with this improved scheme. First is the reduced computation time as the number of arithmetic computation required for processing a vector as successive scalar measurements is significantly less than the corresponding number of operations for vector measurement processing. Second advantage is the improved numerical accuracy as avoiding matrix inversion in the implementation of covariance equations improves the robustness of the covariance computations against round off errors.

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