An Exoatmospheric Homing Guidance Law Based on Deep Q Network
A homing guidance law for exoatmospheric interceptor based on the Deep Q Network (DQN) algorithm is proposed in this paper. Aiming at the exoatmospheric interception problem, the guidance agent is built with the help of the deep reinforcement learning theory, and the action command is given accordin...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/1544670 |
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| author | Jin Tang Zhihui Bai Yangang Liang Fan Zheng Kebo Li |
| author_facet | Jin Tang Zhihui Bai Yangang Liang Fan Zheng Kebo Li |
| author_sort | Jin Tang |
| collection | DOAJ |
| description | A homing guidance law for exoatmospheric interceptor based on the Deep Q Network (DQN) algorithm is proposed in this paper. Aiming at the exoatmospheric interception problem, the guidance agent is built with the help of the deep reinforcement learning theory, and the action command is given according to the measurement information of the exoatmospheric interceptor for the accurate interception of the target. The homing guidance problem is first transformed into a Markov decision process, and a three-dimensional (3D) interception scenario is established. Then, the reward function considering the line-of-sight (LOS) rate and the final zero-effort-miss (ZEM) is designed, and the homing guidance problem is transferred to the reinforcement learning framework. After that, DQN is utilized to solve the exoatmospheric interception problem, and the guidance agent is obtained through a large amount of training. Finally, the guidance performance of DQN homing guidance law is verified by numerical simulation examples and compared with the classical true proportional navigation (TPN) guidance law. The results show that the guidance performance of the homing guidance law is better than that of TPN. |
| format | Article |
| id | doaj-art-dca596acd0414b2db977e1a2da3f49bb |
| institution | OA Journals |
| issn | 1687-5974 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-dca596acd0414b2db977e1a2da3f49bb2025-08-20T02:21:35ZengWileyInternational Journal of Aerospace Engineering1687-59742022-01-01202210.1155/2022/1544670An Exoatmospheric Homing Guidance Law Based on Deep Q NetworkJin Tang0Zhihui Bai1Yangang Liang2Fan Zheng3Kebo Li4College of Aerospace Science and EngineeringThe 31102 TroopsCollege of Aerospace Science and EngineeringThe 41st Institute of Forth Academy of Aerospace Science and Technology CorporationCollege of Aerospace Science and EngineeringA homing guidance law for exoatmospheric interceptor based on the Deep Q Network (DQN) algorithm is proposed in this paper. Aiming at the exoatmospheric interception problem, the guidance agent is built with the help of the deep reinforcement learning theory, and the action command is given according to the measurement information of the exoatmospheric interceptor for the accurate interception of the target. The homing guidance problem is first transformed into a Markov decision process, and a three-dimensional (3D) interception scenario is established. Then, the reward function considering the line-of-sight (LOS) rate and the final zero-effort-miss (ZEM) is designed, and the homing guidance problem is transferred to the reinforcement learning framework. After that, DQN is utilized to solve the exoatmospheric interception problem, and the guidance agent is obtained through a large amount of training. Finally, the guidance performance of DQN homing guidance law is verified by numerical simulation examples and compared with the classical true proportional navigation (TPN) guidance law. The results show that the guidance performance of the homing guidance law is better than that of TPN.http://dx.doi.org/10.1155/2022/1544670 |
| spellingShingle | Jin Tang Zhihui Bai Yangang Liang Fan Zheng Kebo Li An Exoatmospheric Homing Guidance Law Based on Deep Q Network International Journal of Aerospace Engineering |
| title | An Exoatmospheric Homing Guidance Law Based on Deep Q Network |
| title_full | An Exoatmospheric Homing Guidance Law Based on Deep Q Network |
| title_fullStr | An Exoatmospheric Homing Guidance Law Based on Deep Q Network |
| title_full_unstemmed | An Exoatmospheric Homing Guidance Law Based on Deep Q Network |
| title_short | An Exoatmospheric Homing Guidance Law Based on Deep Q Network |
| title_sort | exoatmospheric homing guidance law based on deep q network |
| url | http://dx.doi.org/10.1155/2022/1544670 |
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