Sudden, shared CN0 drops
A jammer lowers CN0 on many satellites at once. The flag needs critical CN0 drops in more than 5 % of epochs, together with a low mean CN0 or drops shared across constellations.
jamming_detected
GNSS signal quality · Rust core · Python API
Know how clean your signal is. Every satellite, every epoch.
geoveil-cn0 reads RINEX 2, 3 and 4 observation files and turns carrier-to-noise density into a 0–100 quality score, per-constellation statistics, CN0 skyplots and interference, jamming and spoofing checks. Give it a broadcast navigation file and it also predicts which satellites should be in view.
$
pip install geoveil-cn0
–mean CN0, dB-Hz
–satellites tracked
2.6 sper 24 h file
Signal monitor
BOR1 · 2025-12-31 · real geoveil-cn0 output
Constellation
CN0, dB-Hz
≤30354045≥50
Tracks from broadcast ephemeris, sampled every 5 minutes. Timeline: mean CN0 of all satellites above 10° every 30 s, and the number tracked.
SignalsBOR1 · 24 h · 30 s
Signal strength rises with elevation. How fast is the story.
Mean CN0 in 5° elevation bins for each constellation, from the same BOR1 day. A healthy antenna gives a smooth climb. Dips at mid elevations point to obstructions or multipath, and a flat, low curve points to interference.
| Constellation | Mean CN0 | Std dev | Min – max | Satellites | Observations |
|---|
QualityBUCU · 1 h · 1 Hz
One number per file, five reasons behind it
The quality score weighs signal strength, availability, continuity, stability and constellation diversity. These are the real components for one hour of 1 Hz data from BUCU, Bucharest.
Rating: A ≥ 90 · B ≥ 80 · C ≥ 70 · D ≥ 60 · F below. CN0 quality is 0 at a mean of 30 dB-Hz and 100 at 45 dB-Hz. Stability is 100 at a CN0 standard deviation of 2 dB-Hz and 0 at 10 dB-Hz.
Threats3 detectors
Three checks for a hostile sky
Each detector watches a different signature. Thresholds are part of AnalysisConfig, so a station on a noisy rooftop and one in an open field can be tuned differently.
Sustained degradation
Interference is quieter and more frequent. The flag needs CN0 anomalies, drops beyond the configured thresholds, in more than 1 % of epochs.
interference_detectedinterference_threshold_db
Satellites that should not be there
With a navigation file, the library predicts which satellites are above the horizon. A spoofer replays signals that do not match, so a sustained high share of unexpected satellites raises the flag.
spoofing_detectedanalyze_with_nav
| Check | Signature | Default |
|---|---|---|
| Jamming | Critical drops in > 5 % of epochs, plus mean CN0 < 35 dB-Hz or drops across constellations | critical at interference_threshold_db = 6.0 |
| Interference | CN0 anomalies in > 1 % of epochs, at least 3 | anomaly_sensitivity = 0.5 |
| Spoofing | Unexpected satellites against broadcast ephemeris, sustained over 5 minutes or above 60 % | > 40 % and > 8 satellites |
SpeedXeon E5-2620 v3 · one core
A 24-hour station day in 2.6 seconds
Wall-clock time on public IGS files from 31 December 2025, the same set used for geoveil-mp, on a 2014 server CPU. The analysis runs on one core, so a batch of files scales with the cores you give it. Visibility prediction from broadcast ephemeris is the extra cost of analyze_with_nav.
Stress test
24 hours at 1 Hz: 86,400 epochs of 127 satellites take 129.1 s without navigation and 263.8 s with it, peaking at 14.2 GB.
| File | Epochs × sats | analyze_file | with nav | Peak memory | Quality |
|---|---|---|---|---|---|
| RINEX 2.11 · 24 h · 30 s ZIMM · GPS · 5.4 MB | 2,880 × 32 | 0.14 s | 4.31 s | 104 MB | 66.5 |
| RINEX 3.02 · 24 h · 30 s BOR1 · 6 GNSS · 19.4 MB | 2,880 × 106 | 2.57 s | 7.97 s | 446 MB | 75.7 |
| RINEX 3.05 · 15 min · 1 Hz BUCU · 4 GNSS · 9.6 MB | 900 × 44 | 0.99 s | 2.62 s | 201 MB | 96.9 |
| RINEX 3.05 · 1 h · 1 Hz BUCU · 4 GNSS · 39.9 MB | 3,600 × 52 | 3.78 s | 9.98 s | 739 MB | 96.3 |
| RINEX 3.05 · 24 h · 1 Hz BUCU · 4 GNSS · 948.1 MB | 86,400 × 127 | 129.1 s | 263.8 s | 14.2 GB | 76.4 |
In productionCRNM · 2026-08-14 · 30 s
Running on batch.geoveil-rinex.eu
The GeoVeil batch platform runs geoveil-cn0 on every station day it receives. These screenshots show one day of the CRNM station, a Trimble Alloy receiver. Select a chart to see it full size.
Explore the platformNo sign-in needed to browse.
APIPython 3.9+
A station report in six lines
Install from PyPI, point it at a RINEX file, and read plain Python values back. Wheels for Linux, Windows and macOS.
import hatanaka from geoveil_cn0 import AnalysisConfig, CN0Analyzer obs = hatanaka.decompress_on_disk("BOR100POL_R_20253650000_01D_30S_MO.crx.gz") # geoveil-cn0 reads plain RINEX nav = hatanaka.decompress_on_disk("BRDC00IGS_R_20253650000_01D_MN.rnx.gz") analyzer = CN0Analyzer(AnalysisConfig(min_elevation=10.0, time_bin_seconds=60)) result = analyzer.analyze_with_nav(str(obs), str(nav)) q = result.quality_score print(q.overall, q.rating) # composite 0–100 and its letter print(result.mean_cn0, result.total_satellites) # 45.1 dB-Hz, 106 satellites for BOR1 print(result.get_constellation_summary("Galileo")["mean_cn0"]) tracks = result.get_skyplot_data() # azimuth, elevation and CN0 per satellite
| Member | Returns |
|---|---|
| analyze_file(obs) | CN0 statistics, quality score, anomaly checks |
| analyze_with_nav(obs, nav) | All of the above plus predicted visibility, skyplot and the spoofing check |
| quality_score | overall, rating and the five components |
| get_constellation_summary(name) | Mean, spread and range of CN0, satellites observed and expected |
| get_timeseries_data() | Mean CN0 and satellites tracked per epoch |
| get_skyplot_data() | Azimuth, elevation and CN0 tracks per satellite |
| get_anomalies() | Detected events with time, severity and affected satellites |
| to_json() | The full result as JSON |
LicensePolyForm Noncommercial 1.0.0
Free for science. Licensed for business.
From 0.4.0, geoveil-cn0 is source-available under PolyForm Noncommercial 1.0.0 with an attribution term.
Non-commercial use
Free, with credit
- Research, teaching and personal projects.
- Universities, public research bodies, charities and government agencies.
- Credit "geoveil-cn0 by Miluta Dulea-Flueras" with a link to the repository, and cite it in publications.
Commercial use
Ask for a license
Products, paid services and work done for a company need a separate commercial license. Write to:
miluta.flueras@cartografie.ro
Versions 0.3.9 and earlier remain available under the MIT license. The full terms are in the LICENSE file.
CitationBibTeX
geoveil_cn0.bib
@software{geoveil_cn0_2026,
title = {geoveil-cn0: High-performance GNSS signal quality analysis},
author = {Dulea-Flueras, Miluta},
year = {2026},
version = {0.4.2},
url = {https://github.com/miluta7/geoveil-cn0},
license = {PolyForm-Noncommercial-1.0.0}
}