Air Target Threat Assessment Based on PCNN Neural Network

被引：1

作者：

Yang Jia ^{[1
]}

Lv Mingwei ^{[1
]}

机构：

[1] Shenyang Aircraft Design & Res Inst AVIC, Shenyang 110035, Peoples R China

来源：

PROCEEDINGS OF 2022 INTERNATIONAL CONFERENCE ON AUTONOMOUS UNMANNED SYSTEMS, ICAUS 2022 | 2023年 / 1010卷

关键词：

PCNN neural network; Threat assessment; Aerial target; Air battlefield; Deep learning; Assistant decision;

D O I：

10.1007/978-981-99-0479-2_285

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Air battlefield target threat assessment assists pilots in attack and defense decisions, which is of great significance for future battlefield battle command. Aiming at the problem of air target threat assessment classification, an air target threat assessment model based on PCNN neural network is established, and the simulation training is carried out by using the model. The results show that the model can effectively achieve the classification of air target threat assessment in the aspect of air target threat assessment, provide an idea and method for the future battlefield battle command research, and promote the development and implementation of battlefield target threat assessment system.

引用

页码：3092 / 3102

页数：11

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