Intelligent Threat Assessment Algorithm Based on Pre-Wavelet Transform
Yifan Zheng, Biyin Zhang, Shanqiang Zhang, Qianwen Zhou, Hao Liu, Huihui Helen Wang · 2023
The current warfare situation is increasingly informationized, intelligent, unmanned, and multi-domain. Therefore, it is of great significance to assist the commander in decision-making and realize the automation of the command-and-control system by performing a fast, accurate and reasonable threat assessment based on the relevant situation changes in the rapidly changing battlefield. Many traditional threat assessment algorithms cannot meet the increasing demand in terms of real-time and accuracy. Based on this, a deep learning algorithm model with a pre-wavelet transform module is proposed. The algorithm model can quickly make threat judgments and the judgment results are relatively accurate, and at the same time, it can continuously optimize calculations in the face of ever-changing and complex situations. Then the possible reasons for the good effect of the front-end wavelet transform module are analyzed, and the similarity between wavelet transform and batch normalization is discussed.