3D UAV Wind Mapping for Micro-Condition Flight Planning
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Solution Overview
Problem
Coarsely-grained wind forecasts are inadequate for unmanned aerial vehicles (UAVs) due to their shorter flight distances and varying altitudes, which can lead to unknown wind vectors and increased turbulence, making it challenging to create effective flight plans.
Innovation Solution
A system comprising multiple UAVs equipped with altitude sensors and GPS receivers that determine wind vectors within a region, generating a three-dimensional wind map and correlating it with coarsely-grained forecasts to create a three-dimensional wind prediction map for improved flight planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If coarsely-grained wind forecasts with 0.5° lateral resolution are used for flight planning, then the system is simple and easy to operate, but the wind vector data is insufficient for short-distance unmanned aerial vehicle flights
Solution Approach 1:
The patent divides the region into multiple three-dimensional spaces with finer resolution than the coarsely-grained forecast. Each three-dimensional space contains specific wind vector data collected from unmanned aerial vehicles, allowing precise wind measurements for short-distance flights while maintaining system simplicity through modular data organization.
Solution Approach 2:
The patent transitions from two-dimensional coarse forecast data to three-dimensional wind vector data by adding vertical altitude dimension and collecting data at multiple altitudes. This dimensional expansion provides comprehensive wind information for unmanned aerial vehicles operating at various heights without significantly increasing system complexity.
2Reliability
If coarsely-grained wind forecasts are used for unmanned aerial vehicles, then the system is easy to operate, but wind vectors along flight paths are unknown leading to increased turbulence
Solution Approach 1:
The patent collects and stores wind vector data from multiple unmanned aerial vehicles in advance, building a three-dimensional wind map before flight planning. This preliminary data collection enables accurate flight path planning with known wind vectors, reducing turbulence while maintaining ease of operation through pre-computed wind information.
Solution Approach 2:
The patent uses wind vector data collected from unmanned aerial vehicles during flight to continuously update and refine the three-dimensional wind map. This feedback mechanism improves flight plan accuracy over time while maintaining system simplicity through automated data integration and model updating.
3Adaptability or versatility
If wind data from weather gauges or commercial aircraft is used, then the data source is readily available, but the wind vectors are not suitable for unmanned aerial vehicle flight plans due to altitude differences
Solution Approach 1:
The patent collects wind vector data specifically from unmanned aerial vehicles operating at various altitudes within the region, creating localized three-dimensional wind information tailored to UAV operations. This local data collection ensures wind vectors are appropriate for unmanned aerial vehicle flight conditions while maintaining data availability through distributed sensing.
Solution Approach 2:
The patent creates a three-dimensional wind map that can serve multiple purposes: flight path planning, turbulence prediction, and real-time flight adjustments. This universal wind data structure benefits all unmanned aerial vehicles in the region regardless of specific altitude or mission type, maximizing data applicability while maintaining efficient data collection.
Data Source
AI summary
A system for taking into account micro wind conditions in a region. The system comprises a plurality of aerial vehicles within the region and a wind speed calculator. Each of the plurality of aerial vehicles has an altitude sensor and a GPS receiver. The wind speed calculator is configured to determine wind vectors within the region using measurements from the plurality of aerial vehicles.