Amplitude scintillation detection with geodetic GNSS receivers leveraging machine learning decision tree
Problem
Amplitude scintillation detection normally requires dedicated, costly ionospheric scintillation monitoring receivers (ISMRs).
Why it matters
Dedicated ISMRs are expensive, while common geodetic GNSS receivers are abundant and cheap.
What the AI did
A pre-trained machine learning decision tree uses the scintillation index computed from carrier-to-noise data and elevation angles at 1-Hz to detect amplitude scintillation with ordinary geodetic GNSS receivers.
Results
99% accuracy in scintillation detection on real data
Impact
Enables ionospheric scintillation detection with common GNSS receivers, reducing reliance on costly dedicated ISMRs.
Record
| Venue | Satellite Navigation |
|---|---|
| Published | 2024 |
| Work type | article |
| Authors | Wang Li, Yiping Jiang, Hongyuan Ji, Wenqiang Wei |
| Citations | 12 (OpenAlex, at import time) |
| References | 31 |
| Model or method | machine learning decision tree |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1186/s43020-024-00136-7 |
| Open access | gold |
| Keywords | GNSS, ionospheric scintillation, decision tree, amplitude scintillation, detection |
Importance rating
real but narrower advance
Abstract states dedicated ISMRs are costly while common geodetic GNSS receivers are abundant; enabling scintillation detection with cheap hardware is a real but narrower advance.
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