Can Wang, Jingqi Tu, Xizhong Yang, Jun Yao, Tao Xue, Jinyi Ma, Yiming Zhang, Jianliang Ai, Yiqun Dong
{"title":"Explainable Basic-Fighter-Maneuver Decision Support Scheme for Piloting Within-Visual-Range Air Combat","authors":"Can Wang, Jingqi Tu, Xizhong Yang, Jun Yao, Tao Xue, Jinyi Ma, Yiming Zhang, Jianliang Ai, Yiqun Dong","doi":"10.2514/1.i011388","DOIUrl":null,"url":null,"abstract":"<p>In within-visual-range (WVR) air combat, basic fighter maneuvers (BFMs) are widely used. A BFM decision support scheme has been proposed to aid human pilots in the complex air combat engagement. Recent artificial intelligence advances provide novel opportunities for the development of BFM decision support research. This paper commences by establishing an air-combat-engagement database. Key features that pilots rely on for BFM decision-making in WVR air combat are analyzed, which identifies the input and output data essential for the development of the BFM decision support scheme. A Long Short-Term-Memory (LSTM)-based BFM decision support scheme is then proposed to map input (i.e., combat situations) to output (i.e., BFM decision). Additionally, Shapley-Additive-Explanations-based explainability analysis is also employed to assess the importance of each input feature in the LSTM blocks, and to explain the contribution of each feature to the BFM decision. To evaluate the effectiveness of the proposed BFM decision support scheme, WVR air-combat tests are conducted, which justify the effectiveness of the proposed scheme.</p>","PeriodicalId":50260,"journal":{"name":"Journal of Aerospace Information Systems","volume":"43 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Aerospace Information Systems","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.2514/1.i011388","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
引用次数: 0
Abstract
In within-visual-range (WVR) air combat, basic fighter maneuvers (BFMs) are widely used. A BFM decision support scheme has been proposed to aid human pilots in the complex air combat engagement. Recent artificial intelligence advances provide novel opportunities for the development of BFM decision support research. This paper commences by establishing an air-combat-engagement database. Key features that pilots rely on for BFM decision-making in WVR air combat are analyzed, which identifies the input and output data essential for the development of the BFM decision support scheme. A Long Short-Term-Memory (LSTM)-based BFM decision support scheme is then proposed to map input (i.e., combat situations) to output (i.e., BFM decision). Additionally, Shapley-Additive-Explanations-based explainability analysis is also employed to assess the importance of each input feature in the LSTM blocks, and to explain the contribution of each feature to the BFM decision. To evaluate the effectiveness of the proposed BFM decision support scheme, WVR air-combat tests are conducted, which justify the effectiveness of the proposed scheme.
期刊介绍:
This Journal is devoted to the dissemination of original archival research papers describing new theoretical developments, novel applications, and case studies regarding advances in aerospace computing, information, and networks and communication systems that address aerospace-specific issues. Issues related to signal processing, electromagnetics, antenna theory, and the basic networking hardware transmission technologies of a network are not within the scope of this journal. Topics include aerospace systems and software engineering; verification and validation of embedded systems; the field known as ‘big data,’ data analytics, machine learning, and knowledge management for aerospace systems; human-automation interaction and systems health management for aerospace systems. Applications of autonomous systems, systems engineering principles, and safety and mission assurance are of particular interest. The Journal also features Technical Notes that discuss particular technical innovations or applications in the topics described above. Papers are also sought that rigorously review the results of recent research developments. In addition to original research papers and reviews, the journal publishes articles that review books, conferences, social media, and new educational modes applicable to the scope of the Journal.