基于意图识别的空中群目标动态威胁评估  

Dynamic Threat Assessment of Air Swarm Targets Based on Intent Recognition

作　　者：王宇航 董宝良[1] 公超 尚真真 姚康宁 WANG Yu-hang;DONG Bao-liang;GONG Chao;SHANG Zhen-zhen;YAO Kang-ning(North China Institute of Computing Technology,Beijing 100083,China)

机构地区：[1]华北计算技术研究所,北京100083

出　　处：《计算机与现代化》2023年第12期100-104,111,共6页Computer and Modernization

摘　　要：为解决传统威胁评估算法对态势要素随时间变化的忽略所导致的评估准确率下降的问题,本文提出基于意图识别的空中群目标动态威胁评估方法。本方法首先利用长短期记忆网络(Long Short-Term Memory,LSTM)进行意图预测,接着采用注意力机制(Attention)提升意图预测模型的特征学习能力,通过对输入的多维特征进行一定的加权处理,使得不同特征对结果的影响程度不一样,运用Softmax进行意图结果分类,再以级联的方式将意图预测的结果作为威胁评估的重要输入,并结合静态态势要素和当前时刻的动态态势要素利用多层感知机(MLP)进行威胁评估。通过仿真实验表明,对比传统威胁评估方法,基于意图识别的空中群目标动态威胁评估方法结果更准确。In order to solve the problem of the decline of evaluation accuracy caused by the ignorance of situation elements with time by traditional threat assessment algorithms,this paper proposes a dynamic threat assessment method for air swarm targets based on intent recognition.In this method,the Long Short-Term Memory(LSTM)network is first used for intention prediction,and then the attention mechanism is used to improve the feature learning ability of the intention prediction model,and the multidimensional features of the input are weighted to a certain extent,so that the degree of influence of different features on the results is different.Softmax is used to classify the intention results,and then the results of intention prediction are used as important inputs for threat assessment in a cascading manner.Combined with static situation elements and dynamic situation elements at the current moment,multi-layer perceptron(MLP)is used for threat assessment.Simulation experiments show that compared with the traditional threat assessment method,the dynamic threat assessment method for air swarm targets based on intent recognition is more accurate.

关 键 词：意图预测 威胁评估 神经网络 多层感知机 注意力机制 长短期记忆网络 

分 类 号：E919[军事]