Satellite Orbit Estimation Using Onboard Visual Odometry
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Solution Overview
Problem
Current orbit determination methods for satellites rely heavily on ground-based systems, GPS, and cooperative ranging, which are overwhelmed by the increasing number of satellites and face reliability and equipment constraints, necessitating an autonomous and self-supporting solution.
Innovation Solution
The system uses onboard cameras and image processing to capture and analyze images, performing visual odometry, loop closure measurements, and map matching to estimate the satellite's orbit without external input, employing algorithms like Kalman filters and SLAM for trajectory and position determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ground-based tracking systems and GPS are used for orbit determination, then measurement precision is improved, but device complexity and reliance on external systems increase
Solution Approach 1:
The satellite performs orbit determination autonomously using its own onboard camera and processing systems. The satellite captures images of Earth features, performs visual odometry calculations, and determines its own orbit without requiring external ground-based tracking infrastructure or GPS satellites, thereby eliminating reliance on external systems while maintaining measurement precision
Solution Approach 2:
The patent extracts the orbit determination function from external ground-based systems and GPS infrastructure, implementing it directly on the satellite using onboard imaging and processing capabilities. This removes the dependency on complex external tracking networks while achieving autonomous orbit knowledge
2Measurement precision
If ground-based tracking systems are deployed to monitor increasing satellite numbers, then measurement precision is improved, but loss of time and operational efficiency deteriorate due to system overload
Solution Approach 1:
Each satellite independently determines its own orbit using onboard imaging and visual odometry algorithms, eliminating the need for centralized ground-based tracking. This distributed approach allows simultaneous orbit determination for multiple satellites without system overload, as each satellite operates autonomously and processes images locally in real-time
Solution Approach 2:
The centralized ground-based tracking system is segmented into individual autonomous units on each satellite. Instead of one central system tracking all satellites, each satellite performs its own tracking using its camera and onboard processor, dividing the workload and eliminating bottlenecks associated with monitoring increasing satellite numbers
3Device complexity
If autonomous orbit determination is implemented using onboard instruments, then device complexity is reduced, but measurement precision may worsen without external reference systems
Solution Approach 1:
Earth surface features serve as an intermediary reference for the satellite's autonomous navigation. By capturing images of recognizable Earth features and performing visual odometry, the satellite uses these intermediate visual markers to calculate its position and velocity, achieving accurate orbit determination without direct GPS or ground-based tracking input
Solution Approach 2:
The patent replaces traditional mechanical and electronic reference systems (GPS receivers, ground-based radar) with an optical-based visual odometry system. The satellite uses its camera to capture optical images of Earth features and computes orbit parameters through image processing and geometric calculations, substituting complex electronic tracking systems with a simpler optical-mechanical approach
Data Source
AI summary
Disclosed herein are systems and methods for estimating an orbit of a satellite using only images captured by an onboard camera of the satellite. One of the disclosed methods includes: capturing a plurality of images using an onboard camera of the satellite; determining the trajectory, loop closure metrics, and the relative geographic position of the satellite using the plurality of images captured by the onboard camera; and estimating the orbit of the satellite based at least on the determined trajectory, loop closure metrics, and the relative geographic position of the satellite.