Abstract:Facing the increasingly complicated war environment, the anti-interference performance of the infrared seeker needs to be continually improved. To meet this challenge, the research on the anti-interference performance of infrared weapon can provide technical support of the weapon system, which makes the great construction. This paper presents a method to evaluate the anti-interference performance based on random forest method. Through the idea of machine learning, the comprehensive anti-interference performance value of the guidance system is calculated, which provides a new idea for the evaluation of anti-interference performance of infrared imaging seeker. The experimental results show that the algorithm is reliable and accurate, and it can effectively evaluate the anti-interference performance of infrared seeker.
马潮, 陆志沣, 余海鸣, 洪泽华, 杨杰, 乔宇. 红外成像导引头抗干扰性能评估方法研究[J]. 空天防御, 2018, 1(4): 44-47.
MA Chao, LU Zhifeng, YU Haiming, HONG Zehua, YANG Jie, QIAO Yu. Research on Evaluation Method of Anti-interference Performance of Infrared Seeker. Air & Space Defense, 2018, 1(4): 44-47.