基于态势知识提取和权重优化的动态空战态势评估模型

IF 2.1 3区 工程技术 Q2 ENGINEERING, AEROSPACE
Zhifei Xi, Ying-Xin Kou, You Li, Zhanwu Li, Yue Lv
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引用次数: 0

摘要

空战态势评估是目标分配和机动决策的基础。目前的空战态势评估模型,无论是非参数模型还是参数模型,都忽视了态势变化的连续性和时间性,使态势评估结果失去了战术意义。针对当前空战态势评估的不足,结合隐逻辑过程多元回归模型、基于灰色前景理论的权重优化模型、基于自动编码器和极限学习机(AE-ELM)的权重映射模型和基于动态权重在线极限学习机(DWOSELM)的空战态势特征参数预测模型,提出了基于态势知识提取和权重优化的动态空战态势评估模型。首先,考虑空战态势变化的时序性和连续性,引入隐逻辑过程多元回归模型,实现空战态势时间序列数据的分割和空战态势基元的提取。其次,利用基于灰色前景理论的权重优化方法,得到不同空战态势下评价指标的权重。在此基础上,利用 AE-ELM 构建了空战态势特征参数与指标权重之间的动态映射模型。然后,利用动态加权极端学习机建立目标机动轨迹预测模型,预测目标未来位置信息。在此基础上,获得敌我双方的未来态势信息。最后,利用基于正态累积分布的时间权重计算模型确定各时间点态势的重要性。将空战过程中多个时间点的态势信息进行融合,得到当前时间点的综合空战态势评估结果。仿真结果表明,该模型能充分利用历史信息的影响,有效整合多个时刻的空战态势信息,并根据不同飞行员的个体差异生成具有实际战术意义的空战态势评估结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Dynamic Air Combat Situation Assessment Model Based on Situation Knowledge Extraction and Weight Optimization
Air combat situation assessment is the basis of target assignment and maneuver decisions. The current air combat situation assessment models, whether nonparametric or parametric, ignore the continuity and timing of situation changes, making the situation assessment results lose tactical significance. Aimed at the shortcomings of current air combat situation assessment, a dynamic air combat situation assessment model based on situation knowledge extraction and weight optimization was proposed by combining a multiple regression model of hidden logic process, a weight optimization model based on grey prospect theory, a weight mapping model based on autoencoder and extreme learning machine (AE-ELM) and an air combat situation characteristic parameter prediction model based on dynamic weight online extreme learning machine (DWOSELM). Firstly, considering the timing and continuity of air combat situation change, a hidden logic process multiple regression model was introduced to realize the segmentation of air combat situation time series data and the extraction of air combat situation primitives. Secondly, the weight optimization method based on grey prospect theory was used to obtain the weight of the evaluation index under different air combat situations. On this basis, the dynamic mapping model between air combat situation characteristic parameters and the weight of index was constructed by using AE-ELM. Then, the dynamic weighted extreme learning machine was used to build the target maneuver trajectory prediction model, and the future position information of the target was predicted. On this basis, the future situation information between the enemy and us was obtained. Finally, the time weight calculation model based on normal cumulative distribution was used to determine the importance of the situation at each time. The situation information at multiple times in the air combat process was fused to obtain the comprehensive air combat situation assessment results at the current time. The simulation results show that the model can fully exploit the influence of historical information, effectively integrate the air combat situation information at multiple moments, and generate the air combat situation assessment results with practical tactical significance according to the individual differences of different pilots.
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来源期刊
Aerospace
Aerospace ENGINEERING, AEROSPACE-
CiteScore
3.40
自引率
23.10%
发文量
661
审稿时长
6 weeks
期刊介绍: Aerospace is a multidisciplinary science inviting submissions on, but not limited to, the following subject areas: aerodynamics computational fluid dynamics fluid-structure interaction flight mechanics plasmas research instrumentation test facilities environment material science structural analysis thermophysics and heat transfer thermal-structure interaction aeroacoustics optics electromagnetism and radar propulsion power generation and conversion fuels and propellants combustion multidisciplinary design optimization software engineering data analysis signal and image processing artificial intelligence aerospace vehicles'' operation, control and maintenance risk and reliability human factors human-automation interaction airline operations and management air traffic management airport design meteorology space exploration multi-physics interaction.
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