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.
Emerging Trends in Radar: Natural Language Processing
IEEE Aerospace and Electronic Systems Magazine ; 40 , 6 ; 122-126
2025-06-01
1289998 byte
Article (Journal)
Electronic Resource
English
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