Table of Contents Author Guidelines Submit a Manuscript

Application of Machine Learning Algorithms to Antennas and Radars

Call for Papers

This special issue deals with progress in antenna designs and radar signal processing using machine learning algorithms. Antenna designs that require high computational complexity can be addressed by machine learning algorithms such as artificial neural networks. Furthermore, automatic target detection and target classification using radars have been a topic of significance for the defense and surveillance purposes for decades. Recently, owing to the advancement of machine learning algorithms, especially deep-learning technology that enables modeling high-level abstractions in data, many antenna design and radar classification problems can be revisited.

We invite authors to contribute original research articles as well as review articles that stimulate the continuing effort on the application of machine learning algorithms to antennas and radars. We are particularly interested in articles applying cutting-edge machine learning algorithms such as deep-learning algorithms to antenna design/optimization and radar target classification.

Potential topics include but are not limited to the following:

  • Antenna optimization accelerated by machine learning algorithms
  • Antenna design and characteristic analysis by machine learning algorithms
  • Radar target feature extraction for automatic target recognition
  • Radar target classification using machine learning algorithms
  • Radar imagery classification

Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/ijap/mlaa/.

Submission DeadlineFriday, 20 July 2018
Publication DateDecember 2018

Papers are published upon acceptance, regardless of the Special Issue publication date.

Lead Guest Editor

Guest Editors

  • Yang Li, Baylor University, Waco, USA
  • Yeosun Yoon, Hanwha Systems, Seoul, Republic of Korea