机载光电目标识别算法研究

doi:10.7527/S1000-6893.2025.32601

Abstract

Abstract: Airborne electro-optical target recognition technology holds significant application value in modern military fields, yet its performance in complex battlefield environments still faces numerous challenges. This paper provides a systematic review of airborne electro-optical target recognition algorithms based on visible and infrared data, with a focus on analyzing the research status and development trends of key technologies such as multispectral data fusion, deep learning applications, lightweight design, and environmental adaptability. Through the classification and comparison of existing algorithms, this paper summarizes the advantages and limitations of various methods and explores critical issues to be addressed in future research, such as robustness enhancement in complex environments, real-time optimization, and few-shot learning. The aim of this paper is to offer a comprehensive technical reference for researchers in the field of airborne electro-optical target recognition and to provide theoretical support for further research directions.

Key words: Target recognition, Image processing, Deep learning, Airborne, Visible and infrared

CLC Number:

TN219

jun -HUANG Jing ZHANG Shi-Qian WENG. Research on Airborne Electro-Optical Target Recognition Algorithms[J]. Acta Aeronautica et Astronautica Sinica, doi: 10.7527/S1000-6893.2025.32601.

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Research on Airborne Electro-Optical Target Recognition Algorithms

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