Autonomous GPS Orbit Propagation for Offline Positioning
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Solution Overview
Problem
Existing GPS devices rely on network connections for Assistance data, which is not always available, leading to degraded performance and reduced battery life due to the limitations of Keplerian mathematical models in predicting satellite positions beyond a few hours.
Innovation Solution
A GPS device capable of autonomously generating Assistance data using an orbit propagation model, allowing it to predict satellite positions and velocities without external connections, using Seed Data to drive the Propagator module for accurate Synthetic Assistance Data generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If GPS devices use Broadcast Ephemeris data from satellites, then satellite position information can be obtained, but the data is only valid for limited time periods (4-6 hours) and accuracy degrades to about a kilometer within a day
Solution Approach 1:
The system performs preliminary orbit propagation calculations using high-accuracy force models and reference frames before the Broadcast Ephemeris expires. By pre-computing and storing accurate satellite position predictions in the reference frame of the GPS device, the system maintains measurement precision beyond the 4-6 hour validity period without requiring continuous external data updates.
2Reliability
If GPS devices rely on network connections for Assisted-GPS services, then TTFF can be reduced and battery life extended, but service availability is degraded when network connections are unavailable
Solution Approach 1:
The GPS device performs self-service by autonomously generating Assisted-GPS data locally using onboard orbit propagation capabilities. The device uses its own reference frame and stored ephemeris data to compute satellite positions without requiring external network assistance, thereby maintaining service reliability in offline conditions while minimizing TTFF through local computational resources.
3Device complexity
If GPS devices use Keplerian mathematical models for orbit prediction, then computational complexity is reduced, but prediction accuracy degrades beyond a few hours
Solution Approach 1:
The system changes the fundamental parameters of the orbit model by transitioning from simple Keplerian equations to a comprehensive force model that incorporates gravitational effects from multiple bodies (Earth, Moon, Sun), solar pressure, and other perturbations. This parameter transformation enables high-accuracy predictions beyond a few hours while managing computational complexity through selective application of force models based on required precision levels.
4Measurement precision
If GPS devices continuously monitor Broadcast Ephemeris data, then updated satellite position information can be obtained, but battery life is shortened due to continuous processing
Solution Approach 1:
The system performs preliminary orbit propagation calculations and stores the results in advance using efficient force models. By pre-computing satellite positions for extended periods and caching them in the device's reference frame, the system eliminates the need for continuous real-time monitoring and processing, thereby extending battery life while maintaining access to fresh position information through efficient retrieval algorithms.
Data Source
AI summary
A method of predicting a location of a satellite is provided wherein the GPS device, based on previously received information about the position of a satellite, such as an ephemeris, generates a correction acceleration of the satellite that can be used to predict the position of the satellite outside of the time frame in which the previously received information was valid. The calculations can be performed entirely on the GPS device, and do not require assistance from a server. However, if assistance from a server is available to the GPS device, the assistance information can be used to increase the accuracy of the predicted position.