Agent skill · Data & Analytics

matlab-compute-gnss-position

Computes multi-constellation Global Positioning System (GPS) or Global Navigation Satellite System (GNSS) positions from RINEX v3 data using rinexread, gnssmeasurements, receiverposition, and gnssoptions. Filters by constellation, elevation mask, C/N0, and observation code. Reports DOP, scatter RMS, and satellite count. Use when processing GNSS data, computing positions from RINEX files, analyzing accuracy, comparing constellations, or evaluating satellite geometry. Do NOT use for carrier-phase RTK/PPP, IMU fusion, orbit propagation, NMEA streaming, or RINEX v4.

matlabgithub.com/matlabGitHub ↗
claude-codecodexcopilotNOASSERTION
Install
npx skills add matlab/matlab-agentic-toolkit --skill matlab-compute-gnss-position --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 19 KB
Bundled scripts: none
Version: 1.0
Declared author: MathWorks
Path: skills-catalog/robotics-and-autonomous-systems/matlab-compute-gnss-position/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 868
Language: MATLAB

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Multi-Constellation GNSS Positioning Pseudorange-based single-point positioning (SPP) from RINEX v3 data. Supports GPS, GLONASS, Galileo, BeiDou, QZSS, NavIC/IRNSS, and SBAS. **Requires:** Navigation Toolbox R2026a or later. ## When to Use - Processing RINEX observation/navigation files into position solutions - Computing multi-constellation receiver positions - Analyzing positioning accuracy, DOP, and satellite geometry - Comparing single-constellation vs multi-constellation performance - Evaluating the effect of processing options (elevation mask, C/N0, corrections) - Teaching or demonstrating GNSS positioning concepts ## When NOT to Use - Carrier-phase positioning (RTK, PPP, ambiguity resolution) - Sensor fusion with IMU — use `matlab-system-identification` or INS filters - Satellite orbit propagation or scenario simulation — use Aerospace Toolbox - Real-time NMEA stream processing — use `nmeaParser` directly - RINEX v4 files — nested struct format requires different handling ## Must-Follow Rules - **Always use `rinexinfo` first** to confirm RINEX v3 and inspect available constellations/observation codes before reading - **Use the correct observation code per constellation** —

What's inside
Steps it walks through
  1. When to Use
  2. When NOT to Use
  3. Must-Follow Rules
  4. Workflow
  5. Default Observation Codes (Band 1 Preferred)
  6. Processing Defaults
  7. Key Functions
  8. Patterns
  9. GPS-Only Positioning
  10. Multi-Constellation (GPS + Galileo)
  11. Pre-Filter Satellites Missing Navigation Data
  12. C/N0 Signal Strength Filtering
  13. Elevation Mask Filtering
  14. Atmospheric Corrections
Ships with 1 file
  • manifest.yaml
More from matlab-agentic-toolkit
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About this skill
What does the matlab-compute-gnss-position skill do?

Computes multi-constellation Global Positioning System (GPS) or Global Navigation Satellite System (GNSS) positions from RINEX v3 data using rinexread, gnssmeasurements, receiverposition, and gnssoptions. Filters by constellation, elevation mask, C/N0, and observation code. Reports DOP, scatter RMS, and satellite count. Use when processing GNSS data, computing positions from RINEX files, analyzing accuracy, comparing constellations, or evaluating satellite geometry. Do NOT use for carrier-phase RTK/PPP, IMU fusion, orbit propagation, NMEA streaming, or RINEX v4.

How do I install it?

Run `npx skills add matlab/matlab-agentic-toolkit --skill matlab-compute-gnss-position --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From matlab/matlab-agentic-toolkit, a repository with 868 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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