OASIS is a modular and open-access Python toolbox for processing multi-frequency GNSS data and computing ionospheric indices. It was developed to overcome limitations of proprietary or non-standardized tools and to promote scientific transparency and reproducibility in ionospheric research.

OASIS automates the detection and correction of cycle slips and outliers, performs arc-wise geometry-free (GF) leveling, and derives ionospheric indices directly from calibrated observations, without relying on external products such as Differential Code Biases (DCBs) or vertical TEC maps.

• Processes RINEX v2 and v3 files with 15- or 30-second sampling rates.
• Supports GPS and GLONASS constellations (Galileo and BeiDou coming soon).
• Fully autonomous detection of data gaps, cycle slips, and outliers.
• Arc-wise geometry-free leveling of carrier-phase combinations.
• Computation of ionospheric indices: ROTI, ΔTEC, and SIDX.
• No dependency on DCBs or global TEC maps.

• Python 3.8 or higher
• Required libraries (see requirements.txt for exact versions):
  • numpy
  • pandas
  • matplotlib
  • scipy
  • astropy
  • georinex
  • pyproj

To install all dependencies at once:

pip install -r requirements.txt

1. Input: RINEX and SP3 files.
2. Orbit Interpolation: SP3 files are parsed and interpolated.
3. IPP Calculation: Computes the coordinates of the ionospheric piercing point.
4. MW Combination: Melbourne-Wübbena combination is used to identify cycle slips.
5. Screening:
   • Initial residual screening using ∆MW and polynomial fitting.
   • Refined residual analysis defines mini-arcs by sign changes.
6. Geometry-Free Leveling: Performed arc-wise on valid combinations.
7. Index Derivation:
   • ROTI: Standard deviation of ROT (rate of TEC).
   • ΔTEC: Difference between 15-min and 60-min moving averages of GF combinations.
   • SIDX: Mean absolute ROT in a 1-minute window.

1. Define the station code, year, DOY, and directories in main.py.
2. Run the complete pipeline:

python3 main.py

3. Results are saved in structured output folders, organized by station and satellite.

• RNX_CLEAN.py – Prepares and organizes RINEX data.
• RNX_SCREENING.py – Detects outliers and cycle slips using MW combinations.
• RNX_LEVELLING.py – Performs arc-wise geometry-free leveling.
• DTEC_CALC.py – Calculates ΔTEC index.
• SIDX_CALC.py – Calculates the Sudden Ionospheric Disturbance Index.
• SP3_INTERPOLATE.py – Extracts and organizes SP3 orbit data.
• linear_combinations.py, gnss_freqs.py, settings.py, glonass_channels.dat, etc. – Support modules for GNSS frequency handling and coordinate transformation.

• Time series of leveled GF combinations.
• ROT, ROTI, ΔTEC and SIDX per satellite and station.
• Intermediate figures for screening and quality control.

If you use this software in your research, please cite:

Developed by Giorgio Picanço (Ph.D. in Space Geophysics).

For questions or contributions, please visit:
https://github.com/giorgiopicanco/OASIS
or email: [email protected]

The OASIS toolbox is open-source and free to use under the MIT license.