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Emerging Trends in Radar: Natural Language Processing

  • Ram M. Narayanan
  • , Jackson S. Zaunegger
  • , Paul G. Singerman
  • , Muralidhar Rangaswamy

Research output: Contribution to journalArticlepeer-review

Abstract

Advancements in deep learning have significantly enhanced natural language processing (NLP) technologies, leading to the development of large language models that have garnered widespread public interest. While these models offer generalized solutions across various domains, their application to domain-specific problems, such as radar systems, has not been extensively explored. In this article, we illustrate how recent advancements in NLP are applied to develop solutions for several radar-related challenges. We discuss the current state-of-the-art approaches, address the challenges in developing NLP models for radar applications, and identify avenues for future research.

Original languageEnglish (US)
Pages (from-to)122-126
Number of pages5
JournalIEEE Aerospace and Electronic Systems Magazine
Volume40
Issue number6
DOIs
StatePublished - 2025

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science
  • Electrical and Electronic Engineering

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