Robust ground moving target detection for airborne radar using a novel feature-based machine learning approach

DOI10.1016/j.jfranklin.2022.04.031zbMath1492.68127OpenAlexW4225256973MaRDI QIDQ2148462

Rafi Ahmed, B. M. Golam Kibria

Publication date: 24 June 2022

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2022.04.031

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Machine vision and scene understanding (68T45)

Uses Software

• bootstrap

Cites Work

• Unnamed Item
• On Convergence of Kronecker Graphical Lasso Algorithms
• Robust Two-Stage Reduced-Dimension Sparsity-Aware STAP for Airborne Radar With Coprime Arrays

This page was built for publication: Robust ground moving target detection for airborne radar using a novel feature-based machine learning approach