Train GNSS Localization Using Virtual Beacons and Correlation Delay
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Solution Overview
Problem
Existing GNSS positioning systems face challenges in achieving high accuracy and integrity levels, particularly in environments like the railway sector, due to errors such as signal-in-space, propagation, reception, and local errors, which are not adequately addressed by current methods.
Innovation Solution
A method utilizing correlation delays between received GNSS signals and predicted signals from virtual beacons, converting these delays into spatial biases, and comparing them against a predefined threshold to determine the machine's location, ensuring independent integrity without additional sensors, and accounting for a protection radius to manage accuracy errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional GNSS positioning methods are used, then positioning can be achieved, but positioning accuracy is degraded by multiple error sources including signal-in-space errors, propagation errors, reception errors, and local errors
Solution Approach 1:
The patent introduces virtual beacons as intermediary reference points with known positions along the predefined paths. These virtual beacons serve as mediators between the satellite signals and the machine's position determination, enabling correlation-based positioning that is less susceptible to conventional error sources. The virtual beacons provide stable reference signals that help filter out noise and improve both accuracy and integrity.
Solution Approach 2:
The patent changes the fundamental parameter used for positioning from direct signal strength or time-of-flight measurements to correlation delay measurements. By computing correlation delays between received signals and predicted signals at virtual beacon positions, the system transforms the positioning approach to one that is more robust against signal-in-space errors, propagation errors, and other conventional error sources affecting traditional GNSS methods.
2Measurement precision
If correlation power maximization is used to determine position, then position can be estimated, but bias due to received power levels degrades accuracy
Solution Approach 1:
Instead of using correlation power (amplitude-based) to determine position, the patent inverts the approach by using correlation delay (time-based) as the primary metric. This inversion from amplitude to time domain measurement eliminates the bias introduced by variations in received power levels, as correlation delay is independent of signal strength. The method computes the delay between received and predicted signals rather than relying on correlation magnitude.
3Reliability
If additional sensors or installations are added to improve positioning integrity, then reliability increases, but device complexity and cost increase
Solution Approach 1:
The patent enables the GNSS receiver to self-validate its measurements by computing correlation delays with virtual beacons and comparing them against expected values. The system independently assesses the quality and integrity of its own positioning solution without requiring external validation from additional sensors or ground infrastructure. This self-service capability provides SIL4-level integrity assurance using only the standard GNSS receiver and pre-stored virtual beacon data.
Data Source
AI summary
A method for locating a train moving over a set of tracks over which are distributed virtual beacons defined by their geographical coordinates, the train being equipped with an on-board satellite receiver that receives geopositioning signals from satellites S1, . . . ; Ss for each beacon Bj, j=1 to N and each satellite Sk, k=1 to s: the correlation delay, X(Sk, Bj), between the geopositioning signal received by the satellite receiver from Sk and the theoretical geopositioning signal that should, according to computations, have been received from Sk for Bj is computed; a value representative of the correlation delay X(Sk, Bj) is converted into a distance, ΔSBj,Sk, by multiplying this representative value by c and dividing it by the cosine of the elevation elk of Sk; then MSBBj=MAXk=1 to s{ΔSBj,Sk} is determined then the MSBBj, j=1 to N, are compared with a predefined threshold MSBREF: according to this comparison, if only one beacon has a maximum spatial bias MSBBj less than MSBREF, this beacon is then detected as the one at which the train is to be found.