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Code accompanying "Transmit and Receive Sensor Selection Using the Multiplicity in the Virtual Array" by Ids van der Werf, Costas A. Kokke, Richard Heusdens, Richard C. Hendriks, Geert Leus, and Mario Coutino

Home Page: https://eusipco2024.kokke.eu/

License: GNU General Public License v3.0

HTML 2.83% Python 11.72% Jupyter Notebook 85.45%
active-sensing cramer-rao-bound eusipco multiplicity redundancy sensor-selection tno tudelft eusipco2024 array-processing

eusipco2024's Introduction

Transmit and Receive Sensor Selection Using the Multiplicity in the Virtual Array

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DOI

By Ids van der Werf, Costas A. Kokke, Richard Heusdens, Richard C. Hendriks, Geert Leus, and Mario Coutino.

Code accompanying our submission to the 32nd European Signal Processing Conference (EUSIPCO 2024).

Abstract

The main focus of this paper is an active sensing application that involves selecting transmit and receive sensors to optimize the Cramér-Rao bound (CRB) on target parameters. Although the CRB is non-convex in the transmit and receive selection, we demonstrate that it is convex in the virtual array weight vector, which describes the multiplicity of the virtual array elements. Based on this finding, we propose a novel algorithm that optimizes the virtual array weight vector first and then finds a matching transceiver array. This greatly enhances the efficiency of the transmit and receive sensor selection problem.

Viewing

The notebook can be viewed online by opening it in nbviewer or Google Colab.

Open in nbviewer Open in Colab

Usage

Tested using Pipenv and Jupyter in Visual Studio Code on Ubuntu 22.04. Additionally, XeLaTeX was used to generate the figures.

  1. git clone this repository and cd into the directory.
  2. (optional) export PIPENV_VENV_IN_PROJECT=1 to install Pipenv virtual environments into the current project folder.
  3. pipenv install.
  4. Open this folder in Visual Studio Code.
  5. Install the workspace recommended extension.
  6. Open main.ipynb.

Alternatively, you can try and run a Jupyter server manually, or use Google Colab.

Author(s)

This software has been developed by Costas A. Kokke ORCID logo, Technische Universiteit Delft

License

The contents are licensed under a GPL-3.0 license

Copyright notice:

Technische Universiteit Delft hereby disclaims all copyright interest in the program eusipco2024, written by the Author(s).

Lucas van Vliet, Dean of Faculty of Electrical Engineering, Mathematics and Computer Science, Technische Universiteit Delft.

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