Satellite Terminal Signal Validation via Peer Group Offset Analysis
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Solution Overview
Problem
Satellite communication systems face challenges in accurately diagnosing and detecting issues in satellite terminals before customers notice service interruptions, due to various environmental and technical factors, making it difficult to identify specific problems and optimize terminal performance.
Innovation Solution
A method and system for real-time signal validation that involves determining a subset of satellite terminals, measuring operational statistics, comparing current measurements to prior ones, calculating offsets, and merging these with peer group operational statistics to perform signal validation using updated deviation values, allowing for early detection of potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistical measurement data from satellite terminals is obtained for analysis, then insight into existing problems is improved, but the ability to detect problems before customers notice is insufficient
Solution Approach 1:
The system performs preliminary actions by continuously monitoring operational statistics and comparing them against baseline data before problems manifest to customers. The method proactively identifies degradation trends in signal quality, error rates, and operational parameters, enabling early intervention before service interruptions occur.
Solution Approach 2:
The system implements feedback mechanisms by continuously collecting operational statistics from satellite terminals, comparing current measurements with historical data and peer group performance, and generating alerts when deviations indicate emerging problems. This closed-loop feedback enables real-time detection and response to potential issues.
2Reliability
If multiple operational statistics are measured and compared for each terminal, then diagnostic accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the diagnostic process into distinct components: collecting operational statistics, comparing against baselines, analyzing peer group performance, and generating diagnostics. Each satellite terminal is evaluated independently across multiple statistical dimensions, allowing complex multi-parameter analysis to be broken down into manageable, modular processing steps.
Solution Approach 2:
The system introduces intermediary elements including baseline databases, peer group reference data, and statistical comparison algorithms that mediate between raw operational statistics and diagnostic conclusions. These intermediaries simplify the analysis by providing reference frameworks and automated comparison mechanisms.
Data Source
AI summary
Systems and methods for real-time signal validation are disclosed. In an example embodiment, a subset of terminals in a peer group of satellite terminals is determined. Operational statistics of the satellite terminals in the subset of terminals is measured. Operational statistics of each of the satellite terminals in the subset of terminals is compared to a prior measurement of the same operational statistics. An offset between a current measurement of the operational statistics and the prior measurement of the same operational statistics is determined. An average offset of the current measurement of the operational statistics and the prior measurement of the same operational statistics is determined for the subset of terminals. The average offset for the subset of terminals is merged with a previously determined peer group operational statistic. A signal validation of a terminal is performed using an updated deviation value.