GNSS Satellite Masking Detection Using Pseudo-Distance Residues
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Solution Overview
Problem
Existing GNSS receivers face challenges in accurately determining their position in environments obstructed by obstacles, leading to NLOS situations where indirect signals dominate, causing computational overload and inaccurate positioning due to masking of satellites.
Innovation Solution
A method for detecting satellite masking by continuously receiving and processing pseudo-distance measurements, using a least squares algorithm to analyze residues and form groups of satellites based on signal quality and elevation angles, enabling detection of masked satellites with reduced computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If known methods based on multi-correlators are used for rejecting indirect signals, then the receiver can escape from multipath situation when indirect signals are weak, but the methods become ineffective when indirect signals dominate (NLOS situation)
Solution Approach 1:
The patent changes the detection parameters from signal amplitude comparison to pseudo-distance consistency analysis. By computing pseudo-distances from direct and indirect signals and comparing their differences against a threshold, the system adapts to NLOS conditions where indirect signals dominate, making the detection method effective across both multipath and NLOS situations.
2Measurement precision
If the receiver processes signals from all visible satellites to determine position, then positioning can be achieved in open environment, but positioning accuracy deteriorates when satellites are masked by obstacles
Solution Approach 1:
The patent extracts and identifies masked satellites by detecting inconsistencies in pseudo-distance measurements. Once masked satellites are identified, they are excluded from the positioning calculation, allowing the receiver to determine position using only unmasked satellites with reliable direct signals, thereby maintaining positioning accuracy in hindered environments.
Solution Approach 2:
The patent introduces an intermediary detection mechanism that analyzes pseudo-distance differences between direct and indirect signals. This intermediary analysis layer identifies masked satellites before they corrupt the positioning solution, acting as a filter between the raw signals and the final position calculation.
3Measurement precision
If the system detects and handles masked satellites, then positioning accuracy improves in hindered environment, but computational load increases
Solution Approach 1:
The patent segments the satellite constellation into masked and unmasked groups through detection. By processing satellites in groups and identifying masked ones through pseudo-distance consistency checks, the system reduces the computational burden of handling all satellites uniformly, focusing computational resources only on reliable signals for positioning.
Data Source
AI summary
A method for detecting masking of one or more satellites by an obstacle for a GNSS receiver on board a movable carrier, including receiving, for each one of M satellites, a code pseudo-distance measurement and a variation of carrier pseudo-distances, computing of a definite position of the receiver and a computed position of each satellite, detecting a masking of at least one satellite on the basis of the following operations: computing, at a computation instant and for each satellite, of a computed pseudo-distance and a pseudo-distance reconstructed at a previous time, and detecting masking of at least one satellite by analyzing a magnitude, called residue, computed by applying a least squares algorithm.