GNSS Cross-Correlation Mitigation via Dynamic Overlay Code Removal
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Solution Overview
Problem
In Global Navigation Satellite Systems (GNSSs), weak satellite vehicle signals are often misidentified due to cross-correlation with strong signals, leading to inaccurate position estimation, as existing mask techniques can be too stringent and impair location-estimation accuracy and time.
Innovation Solution
A method that tentatively associates a detected weak signal with a weak-SV pseudo-random noise (PRN) code and a strong signal, modifies the signal to remove the overlay code, and performs cross-correlation analysis to determine alignment between the signals, allowing for accurate identification of signal origins and improved location estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mask techniques are applied to reduce false detections, then false detection rate decreases, but location-estimation accuracy and speed deteriorate
Solution Approach 1:
The patent applies dynamic thresholding where the mask threshold is not fixed but adapts based on the observed cross-correlation values and signal conditions. The system dynamically adjusts the threshold to distinguish true weak signals from cross-correlation artifacts, thereby maintaining high detection accuracy while reducing false positives.
Solution Approach 2:
The patent changes the parameter of the mask threshold from a static value to a dynamically adjusted value based on signal characteristics. By modifying the threshold parameter adaptively, the system resolves the contradiction between reducing false detections and maintaining location-estimation accuracy.
2Reliability
If mask techniques use stringent conditions to avoid false detections, then false detection rate decreases, but location-estimation time increases
Solution Approach 1:
The system dynamically adjusts the mask threshold based on real-time signal conditions and cross-correlation observations. This dynamic adaptation allows the system to use less stringent conditions when appropriate, reducing the time required for location estimation while maintaining reliability.
Solution Approach 2:
The patent performs preliminary analysis of cross-correlation patterns and signal characteristics before applying the mask technique. By pre-characterizing the signal environment and establishing adaptive thresholds in advance, the system reduces the computational burden during actual location estimation, thereby decreasing processing time.
3Reliability
If overlay codes are used in GNSS signals, then signal robustness improves, but cross-correlation values increase causing more false detections
Solution Approach 1:
The patent extracts and removes the overlay code component from the received signal before performing PRN code correlation. By separating the overlay code from the main signal, the system eliminates the source of excessive cross-correlation while preserving the robustness benefits of overlay codes.
Solution Approach 2:
The patent segments the GNSS signal processing into distinct stages: overlay code removal, PRN code correlation, and mask application. This segmentation allows each processing stage to focus on its specific function, reducing interference and improving overall system performance.
Data Source
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AI summary
Methods and systems for evaluating Global Navigation Satellite System (GNSS) signals are provided. Each of a first GNSS signal received by a GNSS receiver and a second GNSS signal received by the GNSS receiver is accessed. The second GNSS signal can have temporal fluctuations weaker than temporal fluctuations in the first GNSS signal. A delay between a sequence in the first GNSS signal and a corresponding sequence signal in the second GNSS signal is estimated and compared to a threshold. Upon determining that the delay exceeds the threshold, a location is estimated using both the first GNSS signal and the second GNSS signal.