Air attack target threat assessment method based on commander experience learning

Abstract

The invention discloses an air attack target threat assessment method based on commander experience learning. The air attack target threat assessment method comprises the steps that factors influencing incoming attack target threat assessment are acquired and quantified; a subjective weight vector of each influence factor is obtained by adopting a link ratio scoring method, an objective weight vector is obtained by adopting an entropy evaluation method, and then a comprehensive weight vector is obtained; using an ideal solution approximation method to obtain the relative approximation degree of the target to the ideal solution, and using the approximation degree from large to small to sort the target threats; adjusting the threat degrees of different targets by adjusting the weights influencing the threat degrees of the incoming targets; and when the manual intervention cannot be met after the weight is adjusted, the adjustment of different target threat degrees is realized by adding membership degree factors for the threat factors. Compared with the prior art, manual intervention factors are dynamically introduced into the threat assessment model, so that the air attack target threat assessment method has the ability of learning experience of a commander.

Description

technical field [0001] The invention relates to the field of weapon system design, in particular to a method for assessing the threat of an air strike target based on commander experience learning. Background technique [0002] At present, the threat assessment methods of targets are mainly divided into two categories. One is mainly qualitative analysis. It is a method for the evaluator to carefully observe and analyze the status and behavior of the evaluation object through natural language. Objective quantitative analysis and rigid division of objective data. The other type is mainly based on quantitative analysis, mainly based on statistical data, using mathematical language to build models, analyzing various indicators and values ​​of objects to give evaluation conclusions, but human thinking is not purely mathematical, it is both stable and The characteristic of randomness. [0003] However, in modern air defense operations, the defensive side is often faced with mult...

AI Technical Summary

Problems solved by technology

[0003] However, in modern air defense operations, the defensive side is often faced with multi-batch, all-airspace, and continuous saturation attacks. The targets are diversified and rapidly evolving, the interference patterns are complex and changeable, and the threats are uncertain. In such a complex environment, traditional engineering The target threat assessment method based on fixed criteria and expert experience in the application lacks flexibility and adaptability, and the credibility and adaptability of target threat assessment in a highly dynamic battlefield environment will be greatly reduced

Although currently in the application, key targets can be designated through manual intervention to change their threat level, but with the sharp increase in the amount of battlefield information and the sharp changes in the situation in the future, it will be difficult for air defense personnel to timely and accurately detect numerous targets in a short period of time. The goal is to make scientific and reasonable threat interventions. Therefore, it is an inevitable trend to design a threat assessment model that can learn the commander's intervention behavior and adaptively update it to adapt to the future battlefield environment.

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