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Satellite Orbital Dynamics Toolkit

Project description

satkit

Satellite astrodynamics in Rust, with full Python bindings.

Build Release License: MIT

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Satkit is a high-performance orbital mechanics library written in Rust with complete Python bindings via PyO3. It handles coordinate transforms, orbit propagation, time systems, gravity models, atmospheric density, and JPL ephemerides -- everything needed for satellite astrodynamics work.

Documentation and tutorials (Python examples, but the concepts and API apply equally to Rust) | Rust API reference

[!NOTE] Version 0.14.1 replaces nalgebra with numeris for all linear algebra (matrices, quaternions, ODE solvers). numeris is a standalone library that unifies these in a single crate, making them available to projects beyond satkit. Performance is equivalent, and all tests pass with matching residuals. If your code uses nalgebra types, enable the nalgebra feature on numeris for zero-cost conversions. Please open an issue if you hit any problems.

Installation

Rust:

cargo add satkit

Python:

pip install satkit

Pre-built wheels are available for Linux, macOS, and Windows on Python 3.10--3.14.

After installing, download the required data files (gravity models, ephemerides, Earth orientation parameters):

import satkit as sk
sk.utils.update_datafiles()  # one-time download; re-run periodically for fresh EOP/space weather

Quick Examples

SGP4 propagation (Python)

import satkit as sk

tle = sk.TLE.from_lines([
    "ISS (ZARYA)",
    "1 25544U 98067A   24001.50000000  .00016717  00000-0  10270-3 0  9003",
    "2 25544  51.6432 351.4697 0007417 130.5364 329.6482 15.48915330299357"
])

pos, vel = sk.sgp4(tle, sk.time(2024, 1, 2))

High-precision propagation (Python)

import satkit as sk
import numpy as np

r0 = 6378e3 + 500e3  # 500 km altitude
v0 = np.sqrt(sk.consts.mu_earth / r0)

settings = sk.propsettings(
    gravity_model=sk.gravmodel.jgm3,
    gravity_degree=8,
    integrator=sk.integrator.rkv98,  # default; also rkv87, rkv65, rkts54
)

result = sk.propagate(
    np.array([r0, 0, 0, 0, v0, 0]),
    sk.time(2024, 1, 1),
    end=sk.time(2024, 1, 1) + sk.duration.from_days(1),
    propsettings=settings,
)

state = result.interp(sk.time(2024, 1, 1) + sk.duration.from_hours(6))

Coordinate transforms (Python)

import satkit as sk

time = sk.time(2024, 1, 1, 12, 0, 0)
coord = sk.itrfcoord(latitude_deg=42.0, longitude_deg=-71.0, altitude=100.0)

q = sk.frametransform.qitrf2gcrf(time)
gcrf_pos = q * coord.vector

Planetary ephemerides (Rust)

use satkit::{Instant, SolarSystem, jplephem};

let time = Instant::from_datetime(2024, 1, 1, 0, 0, 0.0)?;
let (pos, vel) = jplephem::geocentric_state(SolarSystem::Moon, &time)?;

Features

Coordinate Frames

Full IAU-2006/2000 reduction with Earth orientation parameters:

Frame Description
ITRF International Terrestrial Reference Frame (Earth-fixed)
GCRF Geocentric Celestial Reference Frame (inertial)
TEME True Equator Mean Equinox (SGP4 output frame)
CIRS Celestial Intermediate Reference System
TIRS Terrestrial Intermediate Reference System
Geodetic Latitude / longitude / altitude (WGS-84)

Plus ENU, NED, and geodesic distance (Vincenty) utilities.

Orbit Propagation

  • Numerical -- Selectable adaptive Runge-Kutta integrators (9(8), 8(7), 6(5), 5(4)) with dense output, state transition matrix, and configurable force models
  • SGP4 -- Standard TLE/OMM propagator with TLE fitting from precision states
  • Keplerian -- Analytical two-body propagation

Force Models

  • Earth gravity: JGM2, JGM3, EGM96, ITU GRACE16 (spherical harmonics up to degree/order 360)
  • Third-body gravity: Sun and Moon via JPL DE440/441 ephemerides
  • Atmospheric drag: NRLMSISE-00 with automatic space weather data
  • Solar radiation pressure: Cannonball model with shadow function

Time Systems

Seamless conversion between UTC, TAI, TT, TDB, UT1, and GPS time scales with full leap-second handling.

Solar System

  • JPL DE440/DE441 ephemerides for all planets, Sun, Moon, and barycenters
  • Fast analytical Sun/Moon models for lower-precision work
  • Sunrise/sunset and Moon phase calculations

Linear Algebra

SatKit uses numeris for all linear algebra (vectors, matrices, quaternions, ODE integration). If you also use nalgebra in your project, enable the nalgebra feature on numeris for zero-cost From/Into conversions between types:

numeris = { version = "0.5.5", features = ["nalgebra"] }

Cargo Features

Feature Default Description
omm-xml yes XML OMM deserialization via quick-xml
chrono no TimeLike impl for chrono::DateTime

Data Files

Satkit needs external data for gravity models, ephemerides, and Earth orientation. Call update_datafiles() to download them automatically.

Downloaded once: JPL DE440/441 (~100 MB), gravity model coefficients, IERS nutation tables

Update periodically: Space weather indices (F10.7, Ap) and Earth orientation parameters (polar motion, UT1-UTC) -- both sourced from Celestrak.

Testing and Validation

The library is validated against:

  • Vallado test cases for SGP4, coordinate transforms, and Keplerian elements
  • JPL test vectors for DE440/441 ephemeris interpolation (10,000+ cases)
  • ICGEM reference values for gravity field calculations
  • GPS SP3 precise ephemerides for multi-day numerical propagation

142 tests (106 unit + 36 doc-tests) run on every commit across Linux, macOS, and Windows.

Running Tests Locally

Tests require two sets of external data: the astro-data files (gravity models, ephemerides, etc.) and the test vectors (reference outputs for validation). Download both before running:

# Install the download helper
pip install requests

# Download test vectors
python python/test/download_testvecs.py

Then run tests with the environment variables pointing to the downloaded directories:

# Rust tests
SATKIT_DATA=astro-data SATKIT_TESTVEC_ROOT=satkit-testvecs cargo test

# Python tests
SATKIT_DATA=astro-data SATKIT_TESTVEC_ROOT=satkit-testvecs pytest python/test/test.py

Documentation

References

  • D. Vallado, Fundamentals of Astrodynamics and Applications, 4th ed., 2013
  • O. Montenbruck & E. Gill, Satellite Orbits: Models, Methods, Applications, 2000
  • J. Verner, Runge-Kutta integration coefficients

License

MIT

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