UAV Wind Estimation via Ground-Speed and Heading Optimization
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Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges in estimating wind without airflow sensors, as existing methods are prone to measurement noise and computational complexity, making real-time wind determination difficult.
Innovation Solution
UAVs use onboard sensors to determine ground-speed and heading vectors, employing mathematical optimization and aerodynamic models to computationally estimate wind vectors, reducing noise effects and processing demands through kinematic and model-based estimation techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional wind estimation methods are used without airflow sensors, then device complexity is reduced, but measurement precision deteriorates due to noise in sensor measurements
Solution Approach 1:
The patent combines multiple sensor measurements (GPS ground-speed vectors and inertial sensor flight-heading vectors) with aerodynamic models to estimate wind. This merging of data sources and models compensates for the lack of direct airflow sensor measurements, maintaining measurement precision while avoiding additional device complexity
Solution Approach 2:
The patent uses aerodynamic models as an intermediary to relate measurable quantities (ground-speed and flight-heading vectors) to the unmeasured wind vector. This intermediary model enables indirect wind estimation without requiring direct airflow measurements, resolving the contradiction between device simplicity and measurement accuracy
2Measurement precision
If complex optimization algorithms are used to reduce noise effects, then measurement precision improves, but use of energy and computational complexity increase
Solution Approach 1:
The patent applies optimization only to the extent necessary to achieve acceptable wind estimation accuracy. Rather than using excessively complex algorithms, the system performs computational optimization over a defined time window, balancing measurement precision with energy consumption constraints of the UAV
Solution Approach 2:
The system performs preliminary computations by pre-defining the optimization framework and data collection protocols before flight. This preliminary preparation reduces real-time computational burden during flight, thereby reducing energy consumption while maintaining measurement precision
3Measurement precision
If real-time wind estimation is performed with comprehensive optimization, then measurement precision improves, but productivity decreases due to processing time
Solution Approach 1:
The patent performs wind estimation computations at periodic intervals rather than continuously. By optimizing at discrete time steps based on accumulated sensor data, the system achieves accurate wind estimates while reducing computational processing time, thereby maintaining productivity
Solution Approach 2:
The system collects and pre-processes sensor data (ground-speed and flight-heading vectors) before performing the optimization computation. This preliminary data preparation enables faster real-time processing, resolving the contradiction between measurement precision and productivity
Data Source
AI summary
Embodiments are described for determining wind by an airborne aerial vehicle without reliance on direct measurements of airspeed by the vehicle. Instead, wind may be computationally estimated using disclosed techniques for utilizing measurements of only ground-speed and heading, or only measurements of forces experienced by the airborne aerial vehicle during flight. In one technique, samples of ground-speed measurements and corresponding heading measurements of an airborne vehicle are used in a mathematical optimization of a wind-driven hypothesis of deviations between the two types of measurement at each of multiple sampling times. In another technique, an aerodynamic model of an aerial vehicle can be used to adjust parameters of a wind hypothesis in order to achieve a best-fit between predicted and measured forces on the aerial vehicle during flight.