ewgeo 1.1.0

Python code companion to Emitter Detection and Geolocation for Electronic Warfare (Artech House, 2019) and Practical Geolocation for Electronic Warfare Using MATLAB (Artech House, 2022)

Python Companion to Emitter Detection and Geolocation for Electronic Warfare

This repository is a port of the MATLAB software companion to Emitter Detection and Geolocation for Electronic Warfare, by Nicholas A. O'Donoughue, Artech House, 2019.

This repository contains the Python code, released under the MIT License, and when it is complete, it will generate all the figures and implements all the algorithms and many of the performance calculations within the texts Emitter Detection and Geolocation for Electronic Warfare, by Nicholas A. O'Donoughue, Artech House, 2019 and Practical Geolocation for Electronic Warfare using MATLAB, by Nicholas A. O'Donoughue, Artech House, 2022.

The textbooks can be purchased from Artech House directly at the following links: Emitter Detection and Geolocation for Electronic Warfare, and Practical Geolocation for Electronic Warfare using MATLAB Both are also available from Amazon.

Installation

PyPI Install (recommended)

Use pip to install the package from the PyPI repository

pip install ewgeo

All the tools will be installed and available by importing the ewgeo package.

import ewgeo

Local Install

After cloning or downloading the git repository, you can install it locally in any virtual environment.

If the path to your downloaded copy of the repository is <PATH_TO_EWGEO>, then issue the following commands in a terminal window.

cd <PATH_TO_EWGEO>
python3 -m venv .venv
source .venv/bin/activate
python3 -m pip install -e .

This repository has been tested with Python 3.12 and 3.13. We recommend using a virtual environment for package/dependency handling (the virtual environment does not need to be named .venv, however).

Dependencies

This repository is dependent on the following packages, and was written with Python 3.12.

• matplotlib
• numpy
• scipy
• seaborn

Figures

The make_figures/ folder contains the code to generate all the figures in the textbook. The subfolder make_figures/practical_geo generates figures for the second textbook.

To generate all figures, run the file make_figures.py. To run figures for an individual chapter, use a command such as the following:

import make_figures
chap1_figs = make_figures.chapter1.make_all_figures()

Examples

The examples/ folder contains the code to execute each of the examples in the textbook. The subfolder examples/practical_geo has examples from the second textbook.

Utilities

A number of utilities are provided in this repository, under the following modules:

• ewgeo.aoa Code to execute angle-of-arrival estimation, as discussed in Chapter 7
• ewgeo.array_df Code to execute array-based direction-finding and angle-of-arrival estimation, as discussed in Chapter 8
• ewgeo.atm Code to model atmospheric loss, as discussed in Appendix C
• ewgeo.detector Code to model detection performance, as discussed in Chapter 3-4
• ewgeo.fdoa Code to execute Frequency Difference of Arrival (FDOA) geolocation processing, as discussed in Chapter 12.
• ewgeo.hybrid Code to execute hybrid geolocation processing, as discussed in Chapter 13.
• ewgeo.noise Code to model noise power, as discussed in Appendix D.
• ewgeo.prop Code to model propagation losses, as discussed in Appendix B.
• ewgeo.tdoa Code to execute Time Difference of Arrival (TDOA) geolocation processing, as discussed in Chapter 11.
• ewgeo.triang Code to model triangulation from multiple AOA measurements, as discussed in Chapter 10.
• ewgeo.tracker Code to track emitter position over time using a Kalman filter, as discussed in Chapter 9.
• ewgeo.utils Generic utilities, including numerical solvers used in geolocation algorithms.

Feedback

Please submit any suggestions, bugs, or comments as issues in this git repository.