Aceinna/gnss-ins-sim

Health v2 · maintenance only

Adoption not part of the score

1485 stars · 376 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library for simulating GNSS/INS integrated navigation systems. It generates reference trajectories and synthetic IMU, GPS, odometer, and magnetometer sensor data, runs user-supplied navigation algorithms, and plots and summarizes results.

Use cases

• simulate IMU and GPS sensor data for navigation algorithms
• generate motion trajectories for inertial navigation testing
• test and compare sensor fusion algorithms
• compute Allan deviation of gyroscope and accelerometer data
• benchmark strapdown INS integration algorithms
• generate synthetic sensor data from logged files

When to choose

• you need synthetic IMU/GNSS data with realistic error models to develop or validate navigation algorithms
• you want to compare multiple navigation or tilt/fusion algorithms on identical simulated data
• you need Allan variance analysis of inertial sensor data

When to avoid

• you need real-time navigation on actual hardware rather than offline simulation
• you need a full production GNSS receiver or signal-level RF simulation
• you work outside Python and cannot use NumPy/Matplotlib-based tooling

Facets

library · maturity active

simulation data-generation machine-learning math simulation robotics developer-tools python cross-platform gnss imu sensor-fusion inertial-navigation gps trajectory-generation strapdown-ins allan-variance magnetometer odometer algorithms

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markdown · JSON · MCP: product_card(name="Aceinna/gnss-ins-sim")