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, requiring 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 real-time DOP and bandwidth forecasts for improved LEO-PNT and LEO-NTN services.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If complex receivers are used to handle atmospheric drag, gravity changes, signal obscuration, and multipath interference, then navigation and communication service reliability is improved, but device complexity and power consumption increase

Engineering Contradiction:

Improvenavigation and communication service reliabilityVSAvoidreceiver complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

A cloud-based prediction system acts as an intermediary between LEO satellites and ground receivers. The system generates prediction data about satellite positions, signal quality, and potential interference before transmission, allowing receivers to use simpler algorithms for satellite acquisition and tracking while maintaining high reliability in challenging environments with obscuration and multipath effects

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system performs preliminary calculations and predictions of satellite orbits, signal propagation conditions, and interference patterns in advance via cloud computing. This pre-processing reduces the computational burden on ground receivers, enabling them to maintain reliability without requiring complex real-time processing capabilities

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If complex receivers with enhanced processing capability are deployed, then signal tracking accuracy under obscuration and multipath conditions is improved, but power consumption increases

Engineering Contradiction:

Improvesignal tracking accuracyVSAvoidreceiver power consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The cloud-based prediction system serves as an intermediary that pre-calculates satellite ephemeris, signal quality metrics, and interference predictions. Ground receivers use this pre-processed information to achieve accurate signal tracking under obscuration and multipath conditions without requiring high power consumption for complex real-time computations

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system creates simplified copies of complex orbital and propagation models in the form of prediction data products. These copied models are pre-computed in the cloud and transmitted to receivers, which then use lightweight versions of the models to achieve accurate tracking with minimal power consumption

Inventive Principle:

Principle #26Copying

3Measurement precision

If real-time prediction data is continuously transmitted to all receivers, then navigation service accuracy is improved, but data transmission bandwidth and network infrastructure requirements increase

Engineering Contradiction:

Improvenavigation service accuracyVSAvoiddata transmission volume

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The prediction data system segments the service area into geographic regions and divides prediction computations by region. Each receiver only receives prediction data relevant to its location, significantly reducing the volume of data that must be transmitted and processed while maintaining high navigation accuracy for users in each segment

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system provides locally optimized prediction data tailored to specific geographic regions and user contexts. Prediction accuracy and data granularity are adjusted according to local conditions such as urban canyons, terrain features, and expected multipath environments, ensuring high navigation service accuracy without uniformly increasing data transmission volume across all regions

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS12517259B2Utilizing low earth orbit (LEO) satellite data for obscuration and multipath risk analysis

Publication Date: 2026.01.06 SPIRENT COMMUNICATIONS PLC

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.