GNSS Parameter Calibration Using Phase-Compensated Correlation
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Solution Overview
Problem
Existing Global Navigation Satellite System (GNSS) receivers face challenges in accurately correlating local and received signals due to noise and phase changes, particularly in environments with weak signals or multipath effects, which degrade positioning accuracy.
Innovation Solution
The method involves phase-compensated correlation using first and second estimates of system parameters, comparing these estimates to select the one closer to the true value, allowing for longer coherent integration times and improved signal-to-noise ratio, particularly in environments with attenuated GNSS signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional correlation methods are used in GNSS receivers, then the system operates with standard signal processing, but correlation accuracy deteriorates due to noise and phase changes in weak signals
Solution Approach 1:
The system performs preliminary phase compensation using predicted phase evolution based on system parameters (position, velocity, orientation) before conducting correlation. This advance correction of phase changes caused by receiver motion and environmental factors enables more accurate correlation of weak signals by removing harmful phase variations prior to the correlation process
Solution Approach 2:
The system changes the phase parameter of the local signal or received signal based on predicted phase evolution derived from system parameters. By dynamically adjusting the phase compensation according to predicted receiver motion and environmental conditions, the system optimizes correlation accuracy while filtering out noise and multipath effects
2Reliability
If longer coherent integration times are used to improve signal-to-noise ratio, then correlation of weak signals improves, but system complexity increases due to multiple parameter estimates and comparisons
Solution Approach 1:
The system uses a multi-function approach where the same correlation framework processes multiple parameter estimates simultaneously. By comparing correlation results from different parameter estimates (e.g., different position, velocity, or orientation hypotheses) within a unified processing structure, the system achieves reliable signal detection in weak signal environments while managing complexity through efficient resource sharing
Solution Approach 2:
The system performs self-calibration by using the correlation results themselves to validate and refine parameter estimates. The comparison of correlation signals from different parameter estimates allows the system to automatically identify the most accurate parameters without external calibration, enabling longer integration times with controlled complexity
3Measurement precision
If multiple parameter estimates are tested with phase compensation to determine the true value, then positioning accuracy improves, but processing time increases
Solution Approach 1:
The system performs preliminary phase compensation using predicted phase evolution based on system parameters before conducting correlation. This advance correction reduces the need for extensive iterative processing of multiple parameter estimates, as the phase is already corrected based on predicted receiver motion and environmental conditions
Solution Approach 2:
The system uses feedback from correlation results to efficiently validate parameter estimates. By comparing correlation signals from different parameter estimates and using the results to refine subsequent processing, the system achieves high positioning accuracy while minimizing processing time through intelligent early termination and adaptive refinement
Data Source
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AI summary
A method for performing in a positioning, navigation, tracking, frequency- measuring, or timing system is provided. The method comprises: providing first and second estimates of at least one system parameter during a first time period, wherein the at least one system parameter has a true value and/or true evolution over time during the first time period; providing a local signal; receiving, at a receiver, a signal from a remote source; providing a correlation signal by correlating the local signal with the received signal; providing amplitude and/or phase compensation of at least one of the local signal, the received signal and the correlation signal based on each of the first and second estimates so as to provide first and second amplitude-compensated and/or phase-compensated correlation signals corresponding to the first and second estimates of the at least one system parameter during the first time period, and; determining which of the first and second estimates is nearer the true value and/or true evolution over time of the at least one system parameter during the first time period, based on a comparison between the first and second amplitude-compensated and/or phase- compensated correlation signals. A computer readable medium and system are also disclosed.