GNSS Solution Separation Monitoring for Multiple Satellite Failure Detection
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Solution Overview
Problem
Existing methods struggle to detect multiple simultaneous erroneous Global Navigation Satellite System (GNSS) measurements, particularly in scenarios where spoofing affects most or all satellites, and current techniques are inadequate in differentiating between single and multiple satellite failures.
Innovation Solution
A method using solution separation measurement monitoring with Kalman filter residual and state correction monitoring processes to detect multiple erroneous GNSS measurements by computing and comparing residual and state correction magnitudes against predefined or variable thresholds, allowing for the detection of spoofing events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If solution separation technique is used to detect satellite errors, then single satellite errors can be detected and isolated, but multiple satellite failures cannot be differentiated from single satellite errors
Solution Approach 1:
The patent segments the measurement monitoring process into multiple independent monitoring statistics (measurement residual monitoring and state correction monitoring). Each statistic independently evaluates different aspects of measurement consistency, allowing the system to detect both single and multiple satellite failures by analyzing the combined results of these segmented monitoring approaches.
Solution Approach 2:
The patent changes the monitoring parameters from traditional single-statistic approaches to multiple independent statistics with different characteristics. By monitoring both measurement residuals (difference between observed and predicted measurements) and state corrections (adjustments made to the navigation solution), the system gains the ability to differentiate between single and multiple satellite failures through pattern recognition in the monitoring results.
2Device complexity
If measurement monitoring is performed using single INS/GNSS solution, then processing is simplified, but the ability to detect multiple erroneous measurements is reduced
Solution Approach 1:
The monitoring process is segmented into separate independent statistics (measurement residual monitoring and state correction monitoring) that can be computed from the same INS/GNSS solution. This segmentation allows the system to maintain computational efficiency while gaining enhanced detection capability, as each statistic can be independently evaluated without requiring multiple complete solution passes.
Solution Approach 2:
The patent makes the monitoring process universal by designing statistics that can detect both single and multiple satellite failures using the same computational framework. The measurement residual and state correction statistics serve multiple detection purposes simultaneously, eliminating the need for separate monitoring systems for different failure scenarios.
3Measurement precision
If pre-update measurement residual screenings are used, then measurement errors can be detected, but detection capability depends on the order of measurement processing
Solution Approach 1:
The patent implements feedback mechanisms where the monitoring statistics (measurement residuals and state corrections) are computed after the full measurement update process. This feedback approach allows the system to evaluate the overall impact of all measurements on the navigation solution, making the detection process independent of measurement processing order while maintaining high detection precision.
4Ease of operation
If post-update measurement residual screenings are used, then processing order independence is achieved, but spoofing detection capability is reduced due to self-consistent measurement sets
Solution Approach 1:
The patent changes the monitoring approach by introducing state correction monitoring in addition to measurement residual monitoring. While measurement residuals alone may not detect self-consistent spoofing, the state corrections (which represent the actual impact on the navigation solution) provide an additional dimension for detection. The combination of these two parameters restores spoofing detection capability while maintaining processing order independence.
Data Source
AI summary
A method for detecting failure of multiple satellite signals comprises receiving satellite signals in a GNSS receiver; processing the satellite signals in a Kalman filter to produce a navigation solution and sub-solutions; and performing at least one of a residual monitoring process, or a state corrections monitoring process. In the residual monitoring process, for each sub-solution, expected and actual residuals are computed and compared to determine whether the actual residuals are greater than a threshold; multiple erroneous measurements are detected when at least one actual residual is greater than the threshold for each sub-solution. In the state corrections monitoring process, for each sub-solution, an expected and actual magnitude of state corrections are computed and compared to determine whether the actual magnitude of state corrections is greater than a threshold; multiple erroneous measurements are detected when the actual magnitude of state corrections is greater than the threshold for each sub-solution.