LEO Satellite Visibility Forecasting for Obscuration and Multipath
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Solution Overview
Problem
LEO satellites face challenges due to higher atmospheric drag, changing gravity impacts, rapid signal obscuration, and multipath interference, which complicate orbit determination and signal tracking, necessitating complex and power-hungry receivers for navigation and communication services.
Innovation Solution
A system architecture that predicts LEO satellite visibility and signal quality using environmental data, 3D maps, and cloud-based forecasting to determine line-of-sight and non-line-of-sight satellites, providing dilution of precision (DOP) and bandwidth forecasts for improved navigation and communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex receivers are used to track LEO satellites through atmospheric drag and multipath interference, then navigation accuracy is improved, but power consumption and device complexity increase
Solution Approach 1:
The system performs preliminary forecasting of satellite positions, obscuration events, and multipath interference patterns before the receiver needs to track satellites. By pre-computing which satellites will be visible and their expected signal quality, the receiver can be simplified to only track predicted satellites, reducing power consumption while maintaining navigation accuracy
Solution Approach 2:
A cloud-based forecasting service acts as an intermediary between satellite orbit data and the receiver. This service computes complex orbital mechanics, atmospheric drag effects, and multipath predictions, then provides simplified guidance to receivers about which satellites to track and when to expect obscuration events, reducing the computational burden on receiver devices
2Measurement precision
If complex receivers are used to track LEO satellites through atmospheric drag and multipath interference, then navigation accuracy is improved, but device complexity increases
Solution Approach 1:
The forecasting service pre-computes satellite visibility, obscuration events, and multipath interference patterns before the receiver operates. This allows the receiver to be designed with simpler tracking logic, as it only needs to follow pre-determined satellite selections rather than independently solving complex orbital mechanics and interference patterns
Solution Approach 2:
The cloud-based forecasting service serves as an intermediary that handles complex computational tasks (orbital mechanics, atmospheric drag modeling, multipath prediction), allowing the receiver device to remain simple while still achieving high navigation accuracy through the forecast-guided tracking strategy
3Device complexity
If cloud-based forecasting is used to predict satellite visibility and signal quality, then computational requirements at receiver are reduced, but data transmission and processing time increase
Solution Approach 1:
The forecasting service generates predictions in advance of when the receiver needs them, computing satellite visibility and signal quality forecasts before the actual tracking period begins. This pre-computation approach allows forecast data to be transmitted to receivers ahead of time, reducing the impact of data transmission delays on real-time navigation performance
Data Source
AI summary
Disclosed is a method of providing DOP forecasts for LEO navigation for routing of vehicles, aircraft, alerting humans in vehicles, or wireless devices, and bandwidth forecasts for LEO communications. The method includes accessing a 3D map of an area including structure solids and generating cuboids in spaces not contained in the structure solids; and iteratively over time increments, calculating LEO satellites visible from the cuboids using the map and, using at least the calculated visibility, determining forecasts for the cuboids at the time increments. Also included is compressing the determined forecast spatially and temporally; and distributing the compressed DOP forecast via a CDN, responsive to queries from requestors. Systems of the requestors can take into account the forecast for routing vehicles or alerting humans in vehicles to a predicted navigation impairment. Risk analysis is applied to improving computation and distribution of forecasts. Forecasts are applied to satellite deployment.