Autonomous Space Vehicle Navigation Using Extended Kalman Filter
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current space situational awareness systems require active ground-based assets for navigation of space vehicles, which is costly and inefficient, especially beyond the GPS 12-hour orbit radius, and rely on prior knowledge of tracker position and velocity to determine target position and velocity.
Innovation Solution
Reconfiguring the Extended Kalman Filter to include states for both target and tracker vehicles, allowing simultaneous estimation of position and velocity from line-of-sight measurements within a known gravitational field, eliminating the need for prior knowledge of tracker position and velocity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ground-based assets are used for space vehicle navigation, then navigation accuracy is improved, but system cost and complexity increase
Solution Approach 1:
The patent implements autonomous navigation where the space vehicle uses its own onboard optical tracker to perform line-of-sight measurements of celestial bodies and other space vehicles. The Extended Kalman Filter processes these measurements to self-determine the vehicle's position and velocity without requiring ground-based asset intervention, making the system self-sufficient.
Solution Approach 2:
The patent extracts the navigation function from ground-based infrastructure and relocates it to the space vehicle itself. By removing the dependency on ground-based radar and GPS systems, the navigation capability is embedded within the space vehicle using only lightweight onboard sensors and computational algorithms.
2Extent of automation
If GPS is used for autonomous navigation, then autonomy is improved, but operational range is limited
Solution Approach 1:
The patent creates a universal navigation system that works both within and beyond GPS coverage. The optical tracker-based EKF can process line-of-sight measurements to determine position and velocity in any environment where celestial bodies or other space vehicles are visible, making the system adaptable to deep space operations, lunar missions, and Mars exploration where GPS signals are unavailable.
3Reliability
If larger antennas are used to receive signals beyond GPS orbit, then signal reception is improved, but system mass increases
Solution Approach 1:
The patent replaces the mechanical GPS antenna system with an optical measurement system using an optical tracker. Instead of receiving electromagnetic signals from GPS satellites through large antennas, the system uses optical sensors to measure line-of-sight angles to celestial bodies and space vehicles, processing these measurements through the EKF to derive position and velocity information without requiring heavy antenna infrastructure.
4Measurement precision
If prior knowledge of tracker position and velocity is required, then estimation accuracy is improved, but system autonomy is reduced
Solution Approach 1:
The patent applies preliminary gravitational modeling to establish the dynamic relationship between the tracker and target vehicles. By pre-computing the gravitational field effects and incorporating them into the EKF state transition model, the system can accurately estimate target position and velocity from line-of-sight measurements alone, without requiring prior knowledge of the tracker's own state, thus maintaining autonomy while preserving accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables passive and autonomous navigation of space vehicles by providing accurate position and velocity information of both tracker and target vehicles, reducing system mass and cost, and maintaining performance even in deep space environments.
Implementation Method 1
Both vehicles must follow trajectories in an inertial frame of reference through the field of a body having a known gravitational model
Data Source
AI summary
It is presumed and commonly accepted by those skilled in the art of satellite navigation and Kalman filter design that the filter must be provided with the tracker position and velocity a priori in order to determine target position and velocity. Indeed, it is generally asserted that without a priori knowledge (known or measured values) of the tracker position and velocity, line of sight measurements between satellites do not contain adequate information to infer target states. Passive and autonomous navigation of space vehicles without a priori values for the position and velocity of either the target or tracker vehicle is achieved by reconfiguring the extended Kalman filter, or more generally any predictor/correction class filter, to include states for both the target and tracker vehicles. The target and tracker vehicles must both follow trajectories in an inertial frame of reference through the gravitational field of a gravitational body having a known gravitational model. The reconfigured filter simultaneously estimates the position and velocity of both tracking and target space-based vehicles from line-of-sight measurements.