GPS Navigation Weighted Least Squares Fusion

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Solution Overview

Problem

Conventional GPS-based relative navigation systems are inadequate for accurately calculating the position, velocity, and acceleration of aircraft in adverse weather and terrain conditions, particularly when operating between moving vehicles, due to limitations in processing multiple measurement types and requiring multiple measurements of the same type for optimal solutions.

Innovation Solution

A GPS-based airborne navigation system that fuses different types of measurement data using a weighted least squares algorithm to determine the covariance matrix, selecting the measurement type with the smallest variance for each satellite to minimize errors in position, velocity, and acceleration calculations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional GPS-based relative navigation systems use traditional methods requiring four measurements of the same type, then optimal solutions can be achieved, but processing time increases and speed decreases

Engineering Contradiction:
Improveposition calculation accuracyVSAvoidprocessing time
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent combines multiple different GPS measurement types (code range, carrier phase, wide lane phase, narrow lane phase) into a unified weighted least squares solution. Instead of requiring four measurements of the same type, the system fuses measurements from different types, allowing optimal position solutions to be achieved with fewer measurements and reduced processing time while maintaining accuracy.

Inventive Principle:
Principle #5Merging (Combining)

2Device complexity

If conventional systems use a single measurement type in weighted least squares position solution, then processing is simpler, but measurement precision and reliability decrease

Engineering Contradiction:
Improveprocessing complexityVSAvoidposition solution accuracy
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent changes the parameters being measured by utilizing multiple different GPS measurement types (code range, carrier phase, wide lane phase, narrow lane phase) with different characteristics. Each measurement type has different variance properties, and the weighted least squares algorithm optimally combines these diverse parameters to achieve superior position solution accuracy compared to using a single measurement type.

Inventive Principle:
Principle #35Parameter changes

3Measurement precision

If conventional methods require four measurements of the same type, then optimal solutions are available, but the system cannot provide satisfactory results for relative position estimation between moving vehicles

Engineering Contradiction:
Improveoptimal solution qualityVSAvoidrelative position estimation capability
Core Design Contradiction:
Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent creates a universal position solution method that works effectively for both stationary and moving vehicle applications. The weighted least squares algorithm that fuses multiple GPS measurement types provides satisfactory results for relative position estimation between moving vehicles (aircraft and ship) while also maintaining optimal solution quality for traditional applications, making the system versatile across different operational scenarios.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP2054737B1Method for fusing multiple GPS measurement types into a weighted least squares solution
Publication Date: 2014.09.24 SIERRA NEVADA CORP
  • EP2054737B1 patent drawingFigure 1
  • EP2054737B1 patent drawingFigure 2
  • EP2054737B1 patent drawingFigure 3

AI summary

A method of calculating position data for an airborne aircraft using a GPS-based airborne navigation system includes the processing of a position component of a relative state function by fusing a plurality of different types of measurement data available in the GPS-based system into a weighted least squares algorithm to determine an appropriate covariance matrix for the plurality of different types of measurement data.