Satellite-Orbit-Prediction

Programs for the prediction of satellite orbit in Python.

@author Junkang Huang huangjk8@mail2.sysu.edu.cn

simulation.py:

​ Main file for the prediction.

​ Run the following order in a console:

python simulation.py

​ First enter the relative path of the CPF file of a satellite, then enter the number of data points you want to use (should be smaller than total number of data in the file).

​ Or you can choose to use SGP4 algorithm with TLE input to get a higher precision prediction.

​ Requirement:

• Python 3 environment
• numpy, scipy, matplotlib packages need to be installed
• sgp4, skyfield, astropy packages installed

model.py :

​ Defines parameters, constants and important data structure

• elements: (6,) numpy.array:

  # 0 - Semi-Major Axis (a)

  # 1 - Eccentricity (e)

  # 2 - Inclination (i)

  # 3 - Right Ascension Point (ap)

  # 4 - Perigee (omega)

  # 5 - Mean Anomaly (M)

• basic constants

• parameters of the satellite

• parameters of the Earth

• parameters of the Sun

• parameters of the Moon

• class var: some temporary variables

transform.py :

​ Defines transformation or mathematical calculation functions

• KeplerEquation() : Numerical solution of the Kepler Equation

• RTN2ECI() : get the transform matrix from RTN system to ECI system

• ECEF2ECI(): get the transform matrix from ECEF system to ECI system

• getVar(): transform from elements to satellite states(position and velocity vectors)

• readCPF(): routine to read a CPF file (.jax)

• LagrangeInterpolation(): Lagrange interpolation algorithm implementation

• getData(): CPF files only contain position information. Thus we need to get the velocities using interpolation. And some input data are abandoned near the start and end of the input.

• states2Elements(): transform from states(position and velocity vectors) to elements

predict.py

​ Functions used for prediction, which are called in simulation.py

• predict(): input initial elements and time points, then this function integrates using scipy.solve_ivp() with DOP853 integration algorithm
• change(): update function of elements, used in scipy.solve_ivp().

perturbation.py

​ Perturbations considered in the prediction. This determines the precision of our prediction.

• effect(): total perturbation function
• nonspherical(): the non-spherical perturbation of the Earth, only J2 item considered.
• atmospherical(): the atmospherical drag perturbation of the atmosphere.
• pressure(): the solar radiation pressure perturbation of the Sun
• thirdBody(): calculate the third body acceleration effect of a third body(the Sun and the Moon)
• totalThirdBody(): consider the third body effect of the Sun and the Moon
• forceAnalysis(): calculate the effect on elements from the force on the satellite.

highPrecision.py

​ Some existing algorithms for orbit prediction.

• sgp4Predict(): using SGP4 algorithm