Network RTK Accuracy Estimation via Continuous Interpolation

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Current satellite-aided positioning systems, particularly Global Navigation Satellite Systems (GNSS), face challenges in accurately representing and calculating network-based corrections due to discontinuous and artifact-introduced quality indicators that fail to consider both dispersive and non-dispersive error components across the entire network, leading to suboptimal rover performance and inefficient reference station placement.

Innovation Solution

A method utilizing continuous interpolation techniques that incorporates data from all reference stations within the network to calculate residual dispersive and non-dispersive error values at each rover location, combining with digital elevation models to provide accurate and continuous representations of network RTK accuracy without requiring position data from the rover, thus avoiding boundary discrepancies and irregularities.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If discontinuous quality indicators are used to represent network RTK accuracy, then calculation complexity is reduced, but measurement precision and reliability of accuracy representation deteriorate due to boundary discrepancies and artifacts

Engineering Contradiction:
Improvecalculation complexityVSAvoidaccuracy representation precision
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent applies continuous interpolation techniques to calculate quality indicators across the entire network service area, ensuring that accuracy representation remains continuous without boundary discrepancies. This allows the system to maintain high measurement precision while providing comprehensive coverage throughout the network area.

Inventive Principle:
Principle #20Continuity of useful action

2Speed

If quality indicators consider only local reference station data, then calculation speed is improved, but measurement precision deteriorates due to lack of network-wide error component consideration

Engineering Contradiction:
Improvecalculation speedVSAvoiderror estimation precision
Core Design Contradiction:
SpeedVSMeasurement precision

Solution Approach 1:

The patent segments the network into multiple regions and performs parallel quality indicator calculations for each region, then combines the results. This segmentation approach maintains calculation speed by allowing concurrent processing while ensuring comprehensive network-wide error component consideration through result integration.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent pre-calculates and stores quality indicator components for different network regions, allowing rapid retrieval and combination during actual operations. This preliminary action maintains high calculation speed while ensuring all network-wide error components are considered in the final quality assessment.

Inventive Principle:
Principle #10Preliminary action

3Area of stationary object

If reference station spacing is increased to cover larger service areas, then network coverage area is improved, but reliability of correction quality deteriorates due to larger interpolation distances

Engineering Contradiction:
Improveservice area coverageVSAvoidcorrection quality reliability
Core Design Contradiction:
Area of stationary objectVSReliability

Solution Approach 1:

The patent replaces traditional mechanical interpolation methods with advanced continuous interpolation techniques that can accurately model error distributions over larger distances. This substitution allows the network to maintain high correction quality reliability even with increased reference station spacing and larger service area coverage.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the parameters of the interpolation model to account for larger spatial scales, adjusting the mathematical relationships to maintain accuracy over extended distances. This parameter adjustment enables reliable correction quality assessment even when reference stations are spaced further apart to cover larger areas.

Inventive Principle:
Principle #35Parameter changes

4Measurement precision

If position data from rover is required for quality indicator calculation, then measurement precision is improved, but ease of operation deteriorates due to additional data requirements

Engineering Contradiction:
Improvequality indicator precisionVSAvoidsystem operation simplicity
Core Design Contradiction:
Measurement precisionVSEase of operation

Solution Approach 1:

The patent pre-calculates and stores quality indicator information for the entire network service area before rover operations begin. This preliminary action eliminates the need for real-time rover position data during field operations, maintaining measurement precision while significantly improving ease of operation.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent creates a pre-computed copy of the quality indicator surface that can be queried without requiring actual rover position data. This copying approach allows the system to provide accurate quality information while simplifying rover operation, as the rover only needs to query the pre-computed data rather than participate in calculations.

Inventive Principle:
Principle #26Copying

Data Source

PatentEP2191290B1Method for accuracy estimation of network based corrections for a satellite-aided positioning system
Publication Date: 2012.12.19 LEICA GEOSYSTEMS AG
  • EP2191290B1 patent drawingFigure 1~2
  • EP2191290B1 patent drawingFigure 3~4
  • EP2191290B1 patent drawingFigure 5~6

AI summary

In a method for accuracy estimation of network based corrections for a satellite-aided positioning system, with a network of reference stations code and phase measurements are recorded by the reference stations and transferred to a network processing centre. The measurements are converted to observables and single-differences between a master station and at least one auxiliary station selected for each reference station are calculated. Estimates of single-difference between each reference station and the corresponding master station are generated and slant residuals for each reference station and satellite are calculated by using the difference between calculated single-differences and estimates. Subsequently double- differences are formed by differencing between the slant residuals for each satellite s and the slant residuals of a reference satellite k, leading to zenith residuals calculated by mapping the double-differences to a zenith value. Error values for each reference station are computed by using the zenith residuals and residual dispersive and non-dispersive error values for a potential rover position are estimated by combining residual dispersive and non-dispersive error values of all reference stations. The accuracy of network based corrections is represented graphically by generating a map as a grid of potential rover positions with estimated residual dispersive and non-dispersive error values.