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README.md

Welcome to project SiqNAL

This project aims to provide a reliable open-sourced cubesats tracking following different mechanisms and protocols for transmitting signals that too using very low end receiver i.e Software Defined Radio (SDR) and under limited computation power. As an input it takes output file of sdr (both .dat or .wav) plots waterfall displaying of the signal file showing signal present in different bands of frequency. Further, it applies bandpass filtering to remove undesired frequency and based upon the transmission mechanism used by the transponder on the satellite it follows appropriate tracking pipeline. Right now transponders following Automatic Packet Reporting System (APRS), Beacons or Automatic Picture Transmission (APT) is supported.

Our future goal is to make this project more universal by tracking signals using correlation of signal received from different ground stations but, it will require us to know the preamble part of signal in advance as well as synchronized signals from multiple sources since simple signal correlation gives ambiguous results due to colored gaussian noise.

This project is part of Google Summer of Code 2017 under Aerospaceresearch written by Jay Krishna with Andreas Hornig as mentor.

Installation

This project requires

Python-3.x
Numpy >= 1.12.0
Matplotlib >= 2.0.0
Scipy >= 0.18.1
PyQt4

Make sure you have python3.x and pip installeted on your machine then except for PyQt4 rest of the dependencies can be installed using requirements.txt provided. Open terminal in SiqNAL folder and type

pip3 install -r requirements.txt

Note: Above command may require administrative permissions.

Installation of PyQt4 is system dependent, for some major distributions steps are below.

  1. Ubuntu

     sudo apt-get install python-qt4
    
  2. Windows

    Run installer after downloading from here.

  3. Mac OSX

     brew install qt
     brew install sip
     brew install cartr/qt4/pyqt
    

External Links

For more details you can check this project's detailed explanation on Google Document, documentation or blog post.