Automatic Magnetic Variation Detection for Instrument Landing Systems
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Solution Overview
Problem
Aircraft rely on outdated and potentially inaccurate magnetic variation data for instrument landing systems, which can compromise safety and efficacy during suboptimal conditions due to limited communication and outdated on-aircraft data sources.
Innovation Solution
A method and system that utilize onboard computing resources to determine accurate magnetic variation data by comparing received data with trajectory measurements along an airport's localizer signal, updating the database if a deviation threshold is met, and accumulating data from multiple aircraft for more accurate localized magnetic variation data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If aircraft rely on stored magnetic variation data from databases, then the data can be accessed without continuous communication, but the data becomes outdated and potentially inaccurate over time
Solution Approach 1:
The system continuously monitors actual magnetic variation by measuring trajectory deviations from published approach paths and feeds this information back to update the database. This closed-loop feedback mechanism ensures the database reflects current magnetic conditions rather than relying on static stored data.
Solution Approach 2:
The system uses the aircraft's own navigation and communication capabilities to automatically detect and report magnetic variation changes. The aircraft serves its dual purpose of navigation and data collection, eliminating the need for external surveying operations.
2Measurement precision
If magnetic variation data is updated frequently using new measurement methods, then data accuracy improves, but communication requirements and system complexity increase
Solution Approach 1:
The system makes the aircraft's existing navigation and communication systems multi-functional by using them for both navigation and magnetic variation measurement. The same GPS receiver and communication equipment used for routine navigation also collect magnetic variation data, eliminating the need for dedicated measurement hardware.
Solution Approach 2:
Instead of requiring complex new measurement equipment, the system copies and repurposes existing aircraft systems to perform magnetic variation detection. The trajectory measurements and communication protocols are adapted from standard navigation operations rather than requiring entirely new infrastructure.
3Quantity of substance
If single aircraft measures magnetic variation independently, then communication bandwidth is reduced, but data reliability and accuracy decrease
Solution Approach 1:
The system merges magnetic variation measurement functions across multiple aircraft operating in the same airspace. Individual aircraft contribute their measurements to a collective database, combining the data from multiple sources to achieve higher reliability and accuracy than any single aircraft could provide alone.
Solution Approach 2:
A central database serves as an intermediary that collects, stores, and processes magnetic variation data from multiple aircraft. This intermediary system aggregates measurements from numerous sources and distributes updated magnetic variation information back to aircraft, enabling collaborative data collection without requiring direct communication between all aircraft.
Data Source
AI summary
Systems and methods for automatic magnetic variation detection include receiving, from a magnetic variation database, first magnetic variation data associated with an airport; determining second magnetic variation data based on a published approach associated with the airport and one or more trajectory measurements as an aircraft flies along a centerline of a localizer signal of the airport; determining a difference between the first magnetic variation data and the second magnetic variation data; and if the difference satisfies a deviation threshold, updating the magnetic variation database based at least on the second magnetic variation data.


