Multipath mitigation in GNSS receivers with machine learning models
US12372662B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 9, 2022 |
| Grant date | Jul 29, 2025 |
| Priority date | — |
| Expiry date | Apr 19, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01S19/49
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Machine learning techniques are used, in one embodiment, to mitigate multipath in an L5 GNSS receiver. In one embodiment, training data is generated to provide ground truth data for excess path length (EPL) corrections for a set of received GNSS signals. A system extracts features from the set of received GNSS signals and uses the extracted features and the ground truth data to train a set of one or more neural networks that can produce EPL corrections for pseudorange measurements. The trained set of one or more neural networks can be deployed in GNSS receivers and used in the GNSS receivers to correct pseudorange measurements using EPL corrections provided by the trained set of neural networks.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.