Satellite Target Identification via Autonomous Onboard Processing
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Solution Overview
Problem
Current satellite observation systems rely on human operators for target identification and tracking, which limits real-time detection and response capabilities.
Innovation Solution
A computing system with processing logic that communicates with a fleet of observation satellites, allowing for automatic target identification and tracking by receiving input from a Zone Of Interest database and sending instructions to satellites for observation and data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human operators are used for target identification and tracking, then the system can detect targets in satellite observations, but the detection ability and real-time tracking capability are limited
Solution Approach 1:
The system enables satellites to automatically identify targets and perform tracking operations without human intervention. The satellite compares observed objects with target descriptors in its database, automatically determines whether objects are targets, and executes tracking decisions autonomously, making the system self-sufficient in target identification and tracking functions.
Solution Approach 2:
The patent replaces the mechanical human operator system with an automated electronic processing system. The satellite's onboard computer processes observations, compares them with target descriptors, and makes tracking decisions through electronic algorithms, substituting human cognitive and decision-making processes with automated computational systems.
2Reliability
If human operators process satellite observations, then target detection can be performed, but the response time for real-time tracking is delayed
Solution Approach 1:
The satellite pre-loads target descriptors and identification criteria into its onboard database before missions begin. This preliminary preparation enables the satellite to immediately compare observed objects against known target characteristics without waiting for human operator analysis, significantly reducing response time while maintaining detection reliability.
Solution Approach 2:
The automated system performs target identification and tracking decisions independently without requiring human operator intervention. The satellite autonomously processes observations, compares them with pre-stored target descriptors, and executes tracking actions, eliminating the time delay inherent in human processing while maintaining reliable target detection.
3Productivity
If a fleet of observation satellites is used, then more observations can be performed, but the complexity of selecting and coordinating satellites increases
Solution Approach 1:
Each satellite in the fleet autonomously processes its own observations and independently compares detected objects with target descriptors stored in its onboard database. This self-service approach eliminates the need for complex ground-based coordination and selection algorithms, as each satellite independently determines whether objects are targets and executes tracking decisions without requiring centralized control.
Solution Approach 2:
The patent divides the target identification and tracking function into independent modular units distributed across multiple satellites. Each satellite operates as an autonomous unit with its own processing capabilities and target descriptor database, allowing the fleet to scale in capacity without proportionally increasing coordination complexity, as each segment functions independently.
Data Source
AI summary
A computing system including: a communication link with a plurality of observation satellites; one or more processing logic configured to: receive as input a Zone Of Interest selected in a ZOI database, the input being received at the occurrence of an event; send to one or more observation satellites belonging to the plurality of observation satellites instructions to perform one or more observations of the Zone Of Interest; detect one or more objects in the output of the one or more observations; identify one or more targets from the one or more objects.