Aircraft Meteorological Data Merging via Weighted Transition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing flight management systems face discontinuities in aeroplane trajectories due to outdated wind data, which are not regularly updated and differ from real-time sensor measurements, leading to inaccurate flight predictions.
Innovation Solution
A system that merges real-time atmospheric data from sensors with pilot-input data using a linear weighting method, where the weighting coefficient K is determined by horizontal and vertical distance thresholds, smoothing transitions between data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If raw meteorological data is integrated at a defined frequency, then real-time data availability is improved, but discontinuities and falsified transition calculations between legs occur
Solution Approach 1:
The system performs preliminary action by calculating predicted meteorological data in advance for future positions along the flight path. This predicted data is then merged with actual sensor measurements using a weighting coefficient that transitions from 0 to 1 as the aircraft approaches each measurement point, ensuring continuity is maintained before the discontinuity would occur.
Solution Approach 2:
The patent introduces an intermediary solution by computing predicted meteorological data that acts as a bridge between actual sensor measurements taken at discrete points. This predicted data fills the gaps between measurements, and the weighting coefficient K serves as a mediator that smoothly blends the predicted and actual data, eliminating abrupt transitions and maintaining trajectory continuity.
2Measurement precision
If wind data is updated frequently from sensors, then data accuracy is improved, but discontinuities at boundaries of prediction zones are created
Solution Approach 1:
The system applies parameter changes by dynamically adjusting the weighting coefficient K as a function of distance from the aircraft position. This parameter transition allows the system to smoothly blend between predicted data (when K=0) and sensor measurements (when K=1), eliminating abrupt changes and maintaining data smoothness while incorporating accurate real-time measurements.
3Reliability
If measured meteorological data is regularly integrated, then flight prediction accuracy is improved, but development complexity increases
Solution Approach 1:
The system performs preliminary action by calculating predicted meteorological data in advance for future positions along the flight path. This predicted data is then merged with actual sensor measurements using a weighting coefficient that transitions from 0 to 1 as the aircraft approaches each measurement point, ensuring continuity is maintained before the discontinuity would occur.
Solution Approach 2:
The patent introduces an intermediary solution by computing predicted meteorological data that acts as a bridge between actual sensor measurements taken at discrete points. This predicted data fills the gaps between measurements, and the weighting coefficient K serves as a mediator that smoothly blends the predicted and actual data, eliminating abrupt transitions and maintaining trajectory continuity.
Data Source
AI summary
The invention consists in merging together the predicted and measured meteorological data to supply them to the flight prediction calculation system so as to smooth the discontinuities brought about in the prior art by the simple update which is carried out. This merging is advantageously done by linear weighting of the data, the weighting coefficient depending upon the positioning in vertical and horizontal distances between the predicted point and the aeroplane in relation to chosen thresholds.


