[GSoC’18|OrbitDeterminator|Aakash] Week #5-6 : Implementation of Gibb’s Method

About the Author: Hello guys, I am Aakash Deep. I am an undergraduate student from Indraprastha Institute of Information Technology, Delhi (IIIT-D) in Computer Science and Engineering (CSE). I am a speed-cuber and, my hobby is solving Rubik's Cube.

The post is in the continuation of the series of posts from the past. You can access those post in the following links, blog1 and blog2.

Highlights

  • The database was created for this, a code was written initDatabase.py. The code is responsible for creating a database with all the necessary tables in the database.
  • The database is maintained by the script scraper.py. The script updates tables of the database.
  • The propagation model is implemented. For this, the SGP4 algorithm is used. The algorithm is computing state vectors (a pair of position vector and velocity vector) from the TLE.

Week 5 and 6

The Gibb’s method is implemented. It takes three position vectors as input and after computation gives one position vector and one velocity vector (both as combined also known as a state vector) as output. The OOP concepts are used in the implementation of Gibb’s method. The code is in gibbsMethod.py. By using OOP concepts it supports data abstraction and data encapsulation.

For input, a file is used from /example_data. It contains four attributes which are time, x coordinate, y coordinate and z coordinate. These are the position coordinates at that particular time epoch. As the file contains a lot of position vectors (8000 to be precise), a set of consecutive 3 vectors are used at a time for gibb’s method. Then for the next iteration, the first vector is removed and a new third vector is added to the set. As we are computing state vectors from a set of three vectors, it is obvious that the number of output state vectors is two less than the input position vectors. So, a vector is created by taking the previous length into consideration which holds all the output state vectors. The class also contains a function orbital_elements which converts these state vectors into the orbital elements.

The propagation model, SGP4 is also improved. Previously, the output is not making much sense but after revising it now the velocity vector is making sense. The output of the position vector is coming out to be constant for all the output state vector. Working on position vector in order to get a good output.

Work in Progress

  • Documentation
  • Testing

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