Image Navigation Registration Transfer to Low-Cost Satellites
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Solution Overview
Problem
Current Image Navigation and Registration (INR) systems for satellite remote sensing are expensive and exclusive to high-budget missions, limiting their availability for low-cost space missions that lack sophisticated attitude control capabilities.
Innovation Solution
A system and method that transfers geo-referenced pixel knowledge from an exquisite INR system, such as a GOES satellite, to a low-cost hosted payload using reference imagery and a Kalman Filter for real-time image registration, compensating for orbital motion and attitude changes without requiring advanced attitude control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If exquisite INR systems with sophisticated attitude control capabilities are used, then measurement precision of pixel location and orientation is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses reference imagery from an exquisite INR system as an intermediary to transfer accurate geo-referenced pixel knowledge to the hosted payload. Instead of building complex attitude control systems, the invention mediates the problem by using external reference data (high-quality imagery with known geolocation) to compensate for the lack of sophisticated onboard attitude determination capabilities. The Kalman filter processes this reference imagery to provide continuous, accurate attitude estimates without requiring complex hardware.
Solution Approach 2:
The patent creates a virtual copy of the exquisite INR system's attitude knowledge by processing its reference imagery through a Kalman filter. Rather than physically replicating the sophisticated attitude control hardware, the invention copies the essential functional output (accurate pixel location and orientation data) by mathematically processing the reference imagery to reconstruct attitude information that would otherwise require complex onboard systems.
2Device complexity
If low-cost hosted payloads without sophisticated attitude control systems are used, then device complexity and cost are reduced, but measurement precision of pixel location and orientation deteriorates
Solution Approach 1:
The patent implements a feedback mechanism by continuously processing reference imagery from the exquisite INR system through a Kalman filter. The system uses the known geolocation information in the reference imagery as feedback to continuously update and correct the attitude estimates for the hosted payload. This feedback loop maintains accurate pixel location and orientation measurements despite the absence of sophisticated onboard attitude control systems, as the reference imagery provides ongoing correction data.
3Measurement precision
If reference imagery processing with Kalman Filter is implemented, then INR accuracy is improved for low-cost missions, but use of energy and computational resources increases
Solution Approach 1:
The patent applies partial action by processing only the necessary reference imagery data through the Kalman filter rather than analyzing all possible data streams. The system selectively uses reference imagery from the exquisite INR system that contains the essential geolocation information needed for attitude determination, avoiding unnecessary computational overhead. This partial processing approach achieves sufficient INR accuracy for low-cost missions while managing computational energy consumption at acceptable levels.
Data Source
AI summary
A system and method for improved image navigation and registration on a low cost remote sensing satellite based on reference image data received from an exquisite system.