As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in ...As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in intention recognition,this paper designs an air target intention recognition method(KGTLIR)based on Knowledge Graph and Deep Learning.Firstly,the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism.Meanwhile,the accuracy,recall,and F1-score after iteration are introduced to dynamically adjust the sample weights to reduce the probability of misclassification.After that,an intention recognition model based on Knowledge Graph is constructed to predict the probability of the occurrence of different intentions of the target.Finally,the results of the two models are fused by evidence theory to obtain the target’s operational intention.Experiments show that the intention recognition accuracy of the KGTLIRmodel can reach 98.48%,which is not only better than most of the air target intention recognition methods,but also demonstrates better interpretability and trustworthiness.展开更多
One important mission of the strategic defense is to develop an integrated, layered ballistic missile defense system（BMDS）. Considering the problem of assigning limited defense weapons to incoming ballistic missiles...One important mission of the strategic defense is to develop an integrated, layered ballistic missile defense system（BMDS）. Considering the problem of assigning limited defense weapons to incoming ballistic missiles, we illustrate how defense weapons, ballistic missiles, kill probability and effectiveness of defense（ED） are interrelated and how to understand this relationship for achieving the best allocation plan. Motivated by the queueing theory, in which the available resources are not sufficient to satisfy the demands placed upon them at all times, the layered deployed defense weapon is modeled as a queueing system to shoot Poisson arrived targets. Simultaneously, examples, of optimum intercepts allocation problems under different constraints are presented. The four theorems determine the allocation rules of intercepts to targets that maximize ED or minimize the cost to achieve a required ED.展开更多
基金funded by the Project of the National Natural Science Foundation of China,Grant Number 72071209.
文摘As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in intention recognition,this paper designs an air target intention recognition method(KGTLIR)based on Knowledge Graph and Deep Learning.Firstly,the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism.Meanwhile,the accuracy,recall,and F1-score after iteration are introduced to dynamically adjust the sample weights to reduce the probability of misclassification.After that,an intention recognition model based on Knowledge Graph is constructed to predict the probability of the occurrence of different intentions of the target.Finally,the results of the two models are fused by evidence theory to obtain the target’s operational intention.Experiments show that the intention recognition accuracy of the KGTLIRmodel can reach 98.48%,which is not only better than most of the air target intention recognition methods,but also demonstrates better interpretability and trustworthiness.
基金supported by the Military Graduate Student Foundation of Army
文摘One important mission of the strategic defense is to develop an integrated, layered ballistic missile defense system（BMDS）. Considering the problem of assigning limited defense weapons to incoming ballistic missiles, we illustrate how defense weapons, ballistic missiles, kill probability and effectiveness of defense（ED） are interrelated and how to understand this relationship for achieving the best allocation plan. Motivated by the queueing theory, in which the available resources are not sufficient to satisfy the demands placed upon them at all times, the layered deployed defense weapon is modeled as a queueing system to shoot Poisson arrived targets. Simultaneously, examples, of optimum intercepts allocation problems under different constraints are presented. The four theorems determine the allocation rules of intercepts to targets that maximize ED or minimize the cost to achieve a required ED.
