Satellite Beacon Positioning for GNSS-Jammed Navigation
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Solution Overview
Problem
Navigation systems relying on inertial measurements after GNSS signal spoofing or jamming suffer from increasing positional errors over time.
Innovation Solution
Utilizing an atomic clock-derived time and inertial measurement unit data, combined with satellite beacon data and orbital data, to generate probability density functions (PDFs) for determining geographical position, incorporating angles of arrival and signal strengths to refine positional accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inertial navigation is used after GNSS signal spoofing or jamming, then navigation system can continue to provide position information, but positional errors increase over time
Solution Approach 1:
The patent introduces satellite beacon signals as an intermediary measurement source between GNSS and pure inertial navigation. The system receives beacon data from multiple satellites, extracts position information, and combines it with inertial measurements to correct drift errors without relying on potentially spoofed GNSS signals.
Solution Approach 2:
The system changes the measurement parameters by switching from relying solely on inertial sensor data to incorporating satellite beacon signal parameters (signal strength, angles of arrival, time of arrival). This parameter diversification allows the system to maintain accurate positioning by using multiple independent measurement sources.
2Measurement precision
If satellite beacon data and orbital data are integrated with inertial measurements, then position accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the positioning system into distinct functional modules: beacon signal reception, orbital data management, inertial measurement processing, and integrated position calculation. Each module handles specific data types and operations, making the overall complex system more manageable and maintainable through functional decomposition.
Solution Approach 2:
The system employs a multi-functional processing architecture that can handle multiple data sources (beacon signals, orbital data, inertial measurements) and multiple positioning methods (trilateration, angular measurement, inertial navigation) within a unified framework. This universal approach reduces complexity by avoiding separate dedicated systems for each function.
Data Source
AI summary
Techniques are provided for more accurately determining a geographical position of a body when Global Navigation Satellite System (GNSS) signals are jammed and/or spoofed. In the absence of valid GNSS data, data about beacon signals emitted by a plurality of satellites and each of the plurality of satellites is used with inertial measurement data to estimate the body's geographical position.