Performance Monitoring and Analysis of Down-Link Signal in Balise-based Train Positioning System

Author(s):  
Zhengjiao Li ◽  
Baigen Cai ◽  
Jiang Liu ◽  
Wei Shangguan ◽  
Debiao Lu ◽  
...  
2000 ◽  
Vol 53 (3) ◽  
pp. 403-411 ◽  
Author(s):  
David Harriman ◽  
Steven Leighton ◽  
Bastiaan Ober

This paper discusses the design, development and operation of two tools intended for B-RNAV operations: the enhanced AUGUR system, which was commissioned by EUROCONTROL, and the Global Positioning System (GPS) Performance Monitoring System (GPMS), commissioned by National Air Traffic Services Ltd. (NATS). Both tools were implemented by STASYS Ltd., with support from Delft University on AUGUR algorithm issues. AUGUR, a Predictive GPS Receiver Autonomous Integrity Monitoring (RAIM) system, performs complex calculations and provides an easy-to-interpret Internet-based interface to aid aircraft operators with the use of GPS. Enhancements to AUGUR have been implemented to meet user requests and the requirements of a future Joint Aviation Authorities (JAA) Temporary Guidance Leaflet (TGL) on the airworthiness and operational approval for the use of Area Navigation (RNAV) systems in European airspace designated for Precision RNAV (P-RNAV) operations. The GPMS records output from a variety of GPS UE, has a real-time interface, performs simulations based on logged data, and permits remote analysis. The work carried out consisted of specifying a system to meet the safety study recommendations, choosing hardware, analysing interface requirements, and developing systems and software. These tools are now in place to help with GPS B-RNAV operations, and provide a layer of safety for both en-route flight and GPS-based non-precision approach operations in European airspace.


2017 ◽  
Vol 52 (4) ◽  
pp. 109-120
Author(s):  
Anna Swiatek ◽  
Leszek Jaworski ◽  
Lukasz Tomasik

Abstract The European Geostationary Overlay Service (EGNOS) augments Global Positioning System (GPS) by providing correction data and integrity information for improving positioning over Europe. EGNOS Service Performance Monitoring Support (SPMS) project has assumed establishment, maintenance and implementation of an EGNOS performance monitoring network. The paper presents preliminary results of analyses prepared in Space Research Centre, Polish Academy of Sciences (Warsaw), as one of partners in SPMS project.


Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2346 ◽  
Author(s):  
Tamas Ruppert ◽  
Janos Abonyi

Industry 4.0-based human-in-the-loop cyber-physical production systems are transforming the industrial workforce to accommodate the ever-increasing variability of production. Real-time operator support and performance monitoring require accurate information on the activities of operators. The problem with tracing hundreds of activity times is critical due to the enormous variability and complexity of products. To handle this problem a software-sensor-based activity-time and performance measurement system is proposed. To ensure a real-time connection between operator performance and varying product complexity, fixture sensors and an indoor positioning system (IPS) were designed and this multi sensor data merged with product-relevant information. The proposed model-based performance monitoring system tracks the recursively estimated parameters of the activity-time estimation model. As the estimation problem can be ill-conditioned and poor raw sensor data can result in unrealistic parameter estimates, constraints were introduced into the parameter-estimation algorithm to increase the robustness of the software sensor. The applicability of the proposed methodology is demonstrated on a well-documented benchmark problem of a wire harness manufacturing process. The fully reproducible and realistic simulation study confirms that the indoor positioning system-based integration of primary sensor signals and product-relevant information can be efficiently utilized in terms of the constrained recursive estimation of the operator activity.


Author(s):  
Wei Jiang ◽  
Yizhi Yu ◽  
Kaibin Zong ◽  
Baigen Cai ◽  
Chris Rizos ◽  
...  

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