Aircraft Thermal Estimation Using Recursive Kalman Filtering
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Solution Overview
Problem
Existing methods for detecting and estimating atmospheric thermals are not well-suited for powered aircraft, as they require large memory arrays and are based on batch processing and grid searches, making them unsuitable for small, low-cost microcontrollers and not operable when the propulsion system is running.
Innovation Solution
A recursive extended Kalman filter-based method in polar coordinates that reduces memory requirements and allows updraft detection independent of propulsion system operation, using kinematic and physical parameters of the aircraft to estimate thermal location and strength, and is implemented on low-cost microcontrollers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If batch processing methods with grid search are used to estimate thermal location, then measurement precision is improved, but device complexity and memory requirements increase significantly
Solution Approach 1:
The patent transforms the thermal estimation problem from a batch processing approach to a recursive state estimation approach using Kalman filters. This changes the computational parameters from requiring large memory arrays to using minimal state vectors, resolving the contradiction between precision and device complexity
Solution Approach 2:
The patent replaces the mechanical grid-search batch processing system with a mathematical recursive filter system. This substitution eliminates the need for large memory arrays while maintaining estimation accuracy, directly addressing the memory complexity contradiction
2Measurement precision
If energy variometer data from pure gliders is used, then thermal detection accuracy is improved, but adaptability to powered aircraft is reduced
Solution Approach 1:
The patent creates a universal thermal detection system that works for both pure gliders and powered aircraft by using propulsion-independent updraft measurement. The extended Kalman filter formulation accommodates different aircraft types through parameter adjustments, achieving both precision and adaptability
Solution Approach 2:
The patent separates the thermal detection function from propulsion system dependencies by using only updraft rate measurements. This segmentation allows the same algorithm to function across different aircraft types with varying propulsion characteristics
3Ease of operation
If recursive extended Kalman filter is used instead of batch processing, then ease of operation on low-cost microcontrollers is improved, but measurement precision may be reduced
Solution Approach 1:
The patent optimizes the Kalman filter parameters and state vector dimensions to achieve the best balance between computational efficiency and estimation precision. This parameter optimization allows accurate thermal detection on resource-constrained microcontrollers
Data Source
AI summary
A technique for finding and estimating the locations of atmospheric thermals for the purpose of exploiting the updraft energy to enable the aircraft to remain aloft while reducing or eliminating the need to expend fuel or energy and operational regardless of whether the aircraft is under powered flight or is gliding.