GNSS Railway Speed Interval Estimation Using Doppler Confidence Bounds
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Solution Overview
Problem
Current methods for determining the interval estimation of a railway vehicle's velocity magnitude using GNSS are not tailored to the railway environment, leading to inaccurate estimates, lack of confidence intervals, complex implementation, and difficulties in proving safety in safety-critical applications.
Innovation Solution
A method that directly addresses the railway environment by using Doppler shift measurements from one time instant, the maximum longitudinal rail slope, and design speed to calculate a non-iterative interval estimate of velocity magnitude, ensuring easy implementation and high accuracy, with confidence intervals that cover the actual velocity with the desired probability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If methods for velocity estimation are adapted to railway environment using additional information sources, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The velocity estimation process is segmented into distinct computational steps: obtaining velocity vector estimate from GNSS measurements, calculating covariance matrix, determining confidence ellipsoid, and extracting velocity magnitude interval. This segmentation allows each step to be optimized independently while maintaining overall system manageability.
Solution Approach 2:
The method performs preliminary calculations of the covariance matrix and confidence ellipsoid before final velocity magnitude determination. This preliminary action enables the system to prepare safety-critical information in advance, improving measurement precision while organizing complexity into manageable preparatory stages.
2Measurement precision
If complex estimation methods with multiple time instants are used, then measurement precision is improved, but ease of operation deteriorates due to safety analysis demands
Solution Approach 1:
The method extracts only the necessary velocity magnitude information from the full velocity vector estimate, rather than processing all components. By taking out only the relevant velocity magnitude interval for safety-critical applications, the system maintains precision while reducing operational complexity and safety analysis demands.
Solution Approach 2:
The method uses disposable computational resources by calculating fresh velocity estimates and confidence intervals at each measurement cycle rather than maintaining complex persistent state. This approach achieves high precision through repeated independent calculations while keeping operational simplicity.
3Measurement precision
If fusion of multiple information sources is implemented, then measurement precision is improved, but device complexity increases due to convergence issues
Solution Approach 1:
The method merges GNSS velocity vector measurements with covariance information to produce a unified confidence ellipsoid that directly yields velocity magnitude interval. This merging combines multiple information aspects (position, velocity, uncertainty) into a single integrated estimate, improving precision while avoiding the complexity of separate fusion algorithms.
Solution Approach 2:
The confidence ellipsoid calculation serves multiple functions simultaneously: it provides velocity magnitude estimation, uncertainty quantification, and safety interval determination. This multi-functionality improves measurement precision while reducing device complexity by eliminating the need for separate processing chains for each function.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method provides more accurate and reliable interval estimates of velocity magnitude, reducing complexity and ensuring safety-critical applications meet high integrity standards without requiring extensive external information or numerical methods.
Implementation Method 1
A better precision can be reached using GNSS receivers which provide measurements via Doppler frequency shifts
Data Source
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AI summary
The invention relates to a method for determination of the interval estimation of the velocity magnitude of a railway vehicle using GNSS in the railway environment, during which, initially, an estimate of the vehicle velocity vector, including the confidence ellipsoid are determined in the ECEF WGS84 coordinate system, and subsequently this estimate is transformed into the local END coordinate system; furthermore, from such transformed velocity vector estimate, a 2D estimate of the velocity vector in the horizontal plane is determined, from which a confidence interval of 〈v̂EN,min, v̂EN,max〉 representing the estimate of the horizontal velocity magnitude of the vehicle is determined, and subsequently, an estimate v̂U,max of the maximum possible magnitude of the vertical vehicle velocity is determined from the maximum possible longitudinal slope βmax of the track and the design speed of the vehicle or the estimate of the horizontal velocity magnitude of the vehicle, after which the estimates of horizontal and vertical velocity magnitudes are combined into the final interval estimate of the total magnitude of the railway vehicle velocity, and thus obtained estimate is stored into the memory and/or shown on the display. For the aforementioned method, a subsystem is used, which subsystem contains a GNSS receiver (A) receiving signals from GNSS satellites, which receiver is connected to a bus (F) to which Memory 1 (B), a processor (C), Memory 2 (E) and Memory 3 (G) are connected.