A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition
Air target intention recognition (ATIR) is critical for unmanned systems in modern air defense operations. Through the analysis of typical air defense combat scenarios, first, the paper defines the intention space and intention parameters of air units based on military experience and domain knowledg...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/8/12/765 |
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| author | Li Chen Jing Yang Yuzhen Zhou Yanxiang Ling Jialong Zhang |
| author_facet | Li Chen Jing Yang Yuzhen Zhou Yanxiang Ling Jialong Zhang |
| author_sort | Li Chen |
| collection | DOAJ |
| description | Air target intention recognition (ATIR) is critical for unmanned systems in modern air defense operations. Through the analysis of typical air defense combat scenarios, first, the paper defines the intention space and intention parameters of air units based on military experience and domain knowledge. Then, a rule-based agent for unmanned systems for online intention recognition is proposed, with no training, no tagging, and no big data support, which is not only for intention recognition and parameter prediction, but also for formation identification of air targets. The most critical point of the agent is the introduction and application of a thermal distribution grid graph (TDGG) and virtual grid dictionary (VGD), where the former is used to identify the formation information of air targets, and the latter is used to optimize the storage space and simplify the access process for the large-scale and real-time combat information. Finally, to have a performance evaluation and application analysis for the algorithm, we carried out a data instance analysis of ATIR for unmanned systems and an air defense warfare simulation experiment based on a Wargame platform; the comparative experiments with the classical k-means, FCNIRM, and the sector-based forward search method verified the effectiveness and feasibility of the proposed agent, which characterizes it as a promising tool or baseline model for the battlefield situational awareness tasks of unmanned systems. |
| format | Article |
| id | doaj-art-8b24ccdd5d5c4bb4990b48348a684bee |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-8b24ccdd5d5c4bb4990b48348a684bee2025-08-20T02:00:37ZengMDPI AGDrones2504-446X2024-12-0181276510.3390/drones8120765A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention RecognitionLi Chen0Jing Yang1Yuzhen Zhou2Yanxiang Ling3Jialong Zhang4Test Center, National University of Defense Technology, Xi’an 710100, ChinaNavy Submarine College, Qingdao 266000, ChinaCollege of Data and Target Engineering, Information Engineering University, Zhengzhou 450001, ChinaTest Center, National University of Defense Technology, Xi’an 710100, ChinaTest Center, National University of Defense Technology, Xi’an 710100, ChinaAir target intention recognition (ATIR) is critical for unmanned systems in modern air defense operations. Through the analysis of typical air defense combat scenarios, first, the paper defines the intention space and intention parameters of air units based on military experience and domain knowledge. Then, a rule-based agent for unmanned systems for online intention recognition is proposed, with no training, no tagging, and no big data support, which is not only for intention recognition and parameter prediction, but also for formation identification of air targets. The most critical point of the agent is the introduction and application of a thermal distribution grid graph (TDGG) and virtual grid dictionary (VGD), where the former is used to identify the formation information of air targets, and the latter is used to optimize the storage space and simplify the access process for the large-scale and real-time combat information. Finally, to have a performance evaluation and application analysis for the algorithm, we carried out a data instance analysis of ATIR for unmanned systems and an air defense warfare simulation experiment based on a Wargame platform; the comparative experiments with the classical k-means, FCNIRM, and the sector-based forward search method verified the effectiveness and feasibility of the proposed agent, which characterizes it as a promising tool or baseline model for the battlefield situational awareness tasks of unmanned systems.https://www.mdpi.com/2504-446X/8/12/765air target intention recognitionrule-based agentunmanned systemthermal distribution grid graphvirtual grid dictionary |
| spellingShingle | Li Chen Jing Yang Yuzhen Zhou Yanxiang Ling Jialong Zhang A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition Drones air target intention recognition rule-based agent unmanned system thermal distribution grid graph virtual grid dictionary |
| title | A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition |
| title_full | A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition |
| title_fullStr | A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition |
| title_full_unstemmed | A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition |
| title_short | A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition |
| title_sort | rule based agent for unmanned systems with tdgg and vgd for online air target intention recognition |
| topic | air target intention recognition rule-based agent unmanned system thermal distribution grid graph virtual grid dictionary |
| url | https://www.mdpi.com/2504-446X/8/12/765 |
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