In view of the problems of insufficient confidence in threat assessment of cruise missile, data coupling in multi-attribute decision-making and the accuracy of assessment affected by subjective experience, a threat assessment model, which bases on unsupervised learning and TOPSIS combing with robust principal component analysis improved by smooth \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_{0}$$\end{document} norm, was proposed. The model uses the robust principal component analysis improved by smooth \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_{0}$$\end{document} norm to extract features, realizes decoupling of features, and determines the factors of threat assessment. In allusion to the situation of insufficient acquisition of assessment factors under complex electromagnetic environment, we use MeanShift combing with unsupervised fuzzy c-means clustering algorithm to fit similar features and calculate the threat degree. Using robust principal component to define the weights of TOPSIS can evaluate threat degree more objectively. Finally, the combination of evaluation results is weighted to improve the non-convex generalization ability and the evaluation accuracy of model. The simulation results show that the threat assessment model of cruise missile based on synthetic weights has better accuracy and objectivity, and meets the requirements of threat assessment missions in the battlefield.
Threat Assessment Model of Cruise Missile Based on Unsupervised Learning
Lect. Notes Electrical Eng.
International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021
Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021) ; Chapter : 41 ; 406-415
2022-03-18
10 pages
Article/Chapter (Book)
Electronic Resource
English
Threat assessment , Unsupervised learning , Fuzzy c-means (FCM) , Robust Principal Component Analysis (RPCA) , Technique for Order Preference by Similarity to Solution (TOPSIS) Engineering , Control, Robotics, Mechatronics , Computational Intelligence , Communications Engineering, Networks , Artificial Intelligence
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