Space Debris Radar Tracking Capabilities assessment | Microsat Engineering project
Files relevant to the analysis section is found in graphs.ipynb and momographs.ipynb.
An additional Gradient Boosting and Random Forest test was done in basicML.ipynb. This direction was ultimately not pursued in the final report.
The core functioning of this software was developed in collaboration with another team. The original repository can be found here: https://github.com/tristandijkstra/SpaceDebrisTracking
The tool requires spacetrack log in credentials obtained from https://www.space-track.org/.
git clone git@github.com:tristandijkstra/SmallObjectTracking.git
Add a keys folder with two keys files with names discosweb.txt and spacetrack.txt:
SmallObjectTracking
├───data
├───extract
├───keys
│ ├───discosweb.txt
│ └───spacetrack.txt
.
spacetrack.txt:
username
password
discosweb.txt:
API_KEY
The project has been developed and tested for python 3.9+. An environment can be created using conda:
conda config --add channels conda-forge
conda config --set channel_priority strict
conda env create -f requirements.yaml
or optionally through pip (not tested):
pip install requirements.txt
The package's main functions are shown above. Dashed functions cache the data they collect for faster successive retrieval. Each of the functions contain extensive docstring documentation that details their functioning. Notably, the getTLEsFromLaunches() function allows the user to select many different output methods, some are listed in the example section below. While all functions can be used standalone and have been programmed in the same style, some functioning is only found in getTLEsFromLaunches().
The project's report contains information about the data retrieved.
Exstensive usage can be found in graphs.ipynb, momographs.ipynb and example.ipynb
A basic usage example is shown below:
from extract.extract import getTLEsFromLaunches, getCredentials
from datetime import datetime
start = datetime(2022, 1, 1)
end = datetime(2023, 1, 1)
token = getCredentials(source="discos")
username, password = getCredentials(source="spacetrack")
launchIDs = ["2013-066", "2018-092", "2019-084", "2022-002"]
# standard method, with combined TLEs
discosDataDict, launchesTLEDict = getTLEsFromLaunches(
username,
password,
token,
launchIDs,
start,
end,
combineDiscosAndTLE=True,
collectLaunches=False,
forceRegen=False,
)
print(launchesTLEDict["2013-066"][39416])
# combining everything into one DF
discosDataDict, df = getTLEsFromLaunches(
username,
password,
token,
launchIDs,
start,
end,
combineDiscosAndTLE=True,
collectLaunches=True,
collectAllTLEs=True,
forceRegen=False,
)
print(df)