Multipath Mitigation in Multiband GNSS Receivers
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Solution Overview
Problem
GNSS signals are frequently impaired by multipath effects in urban environments, leading to significant position errors due to signals arriving via multiple paths, making it challenging to accurately calculate positions and synchronize clocks for communication.
Innovation Solution
A method is implemented in mobile devices to identify and mitigate multipath errors by comparing pseudorange measurements from different carrier frequencies, flagging impaired signals, and adjusting their contribution in position calculations, ensuring accurate positioning and clock synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pseudorange measurements from multiple carrier frequencies are compared to identify multipath errors, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the pseudorange measurement process by separating measurements from different carrier frequencies (e.g., L1 and L5 bands) and processing them independently through ionospheric correction. This allows multipath error identification by comparing segmented measurements without requiring complete reprocessing of all signals simultaneously, thus managing device complexity while improving precision.
Solution Approach 2:
The patent introduces an intermediary correction mechanism that uses ionospheric delay models and satellite clock corrections as intermediate steps between raw signal reception and final pseudorange calculation. This intermediary processing layer enables accurate multipath error detection by providing reference values for comparison, improving measurement precision without directly increasing the core receiver complexity.
2Measurement precision
If impaired measurements are excluded or limited in position calculations, then position accuracy is improved, but loss of information increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the weighting of pseudorange measurements based on their identified quality and impairment levels. Instead of binary exclusion, the system modifies measurement parameters (weights) to reflect confidence levels, allowing impaired but not completely invalid measurements to contribute partially to position calculations. This maintains position accuracy while minimizing information loss by utilizing available data to its fullest extent.
Data Source
AI summary
In some aspects, a mobile device is configured to obtain a set of satellite signal measurements through measuring, for each satellite in a first plurality of satellites, a first signal from the satellite in a first frequency band and a second signal from the satellite in a second frequency band. The first plurality of satellites can include at least a first satellite, a second satellite, and a third satellite. The mobile device can determine that at least one measurement in the set of satellite signal measurements is impaired, based on a difference between a measurement of the first signal from a particular satellite (e.g., the first satellite, the second satellite, or the third satellite) and a measurement of the second signal from the particular satellite. A position of the mobile device can then be determined based on non-impaired measurements in the set of satellite signal measurements.