Battlefield Wireless Communication Interference Threat Assessment Method Based on Hierarchical Fuzzy Neural Network

Abstract

A large amount of data information is accumulated for the input and output indicators of the existing interference threat assessment, but the calculation rules and internal relations between the interference threat assessment indicators are difficult to grasp. The evaluation model is difficult to establish and the reasoning process is complicated. This paper proposes a hierarchical fuzzy neural network interference threat assessment. method.Firstly, the concepts and advantages of intuitionistic fuzzy theory and neural network are introduced, and an interference threat assessment index system is established. It make full use of the historically accumulated interference threat database information, and use the layered form of indicators to learn and adjust the parameters of the fuzzy neural network layer by layer, which realizes the learning and memory of the training samples for the interference threat assessment, and uses the fuzzy neural network prediction model to evaluate the current The degree of interference threat. The process of both evaluating indicator rule relationship determination and reasoning evaluation is omitted compared to other threat assessment methods.Finally, the feasibility of the evaluation method is verified by simulation examples and the expected results are achieved.