py A P R i L

Advanced Passive Radar Library

pyAPRiL is a python based signal processing library which implements passive radar signal processing algorithms. All the algorithms are tested and verified through real field measurement data and simulations. The corresponding references are highlited where applicable. Algorithms are researched and developed on real life DVB-T and FM based passive radar systems.

The package is organized as follows:

• pyAPRiL: Main package directory
  • channelPreparation: This file contains wrapper functions for the different algorithms that aims to prepare the reference and the sureveillance signals for the detection stage. Such as reference signal regeneration and clutter cancellation techniques.
  • clutterCancellation: It describes a huge variety of clutter cancellation techniques implemented in the space, time and the space-time domain.
  • hitProcessor: Implements a number of hit and plot processing related functions such as the CFAR and the plot extractor.
  • detector: In this file a number of implementation of the cross-correlation detector can be found.
  • docs: Contains Ipython notebook files with demonstrations.
  • test: Contains demonstration functions.

Installing from Python Package Index:

pip install pyapril

Version history

• 1.0.0 Inital version
• 1.1.0 Automatic detection added (CA-CFAR)

Acknowledgements

This work was supported by the Microwave Remote Sensing Laboratory of BME (Radarlab). A special thank of mine goes to the RTL-SDR site (RTL-SDR) who helped this project becoming mature with the development and testing of the Kerberos SDR.

For further information on passive radars check: tamaspeto.com Tamás Pető 2017-2019, Hungary