Application of DeepSeek in Intelligent Optoelectronic Countermeasure
Bin Qu, Zhulin He, Jie He · Journal of Computing and Electronic Information Management · 2025
With the rapid advancement of war to intelligence, electro-optical countermeasure faces challenges such as high fidelity of situational awareness and high intelligence of game decision-making. Starting from the technical architecture of DeepSeek, this paper systematically discusses its application prospects and challenges in the field of intelligent photoelectric countermeasures. DeepSeek can effectively integrate multi-modal perception, hierarchical reinforcement learning, hardware collaborative optimization and other technologies, realize the ' perception-decision-confrontation ' closed-loop feedback from sensor perception, system decision-making to confrontation behavior, and expand the development trend of deep learning in the electro-optical countermeasure system, in order to eliminate the shortcomings of the current electro-optical countermeasure system, such as long-standing but undetected system response lag and strategy rigidity. Based on the research needs of data-driven, algorithm robustness and computing resource constraints, the new difficulties that DeepSeek will encounter in the application of intelligent photoelectric countermeasure are further discussed and solutions are proposed, such as multi-agent game, brain-like photoelectric cooperation and other technical methods.