Zhongnan Tang, Yujie Wang, Qing-yang Chen, Xixiang Yang
{"title":"多无人机协同攻击过程中目标状态估计与末制导算法研究","authors":"Zhongnan Tang, Yujie Wang, Qing-yang Chen, Xixiang Yang","doi":"10.1109/CACRE50138.2020.9229963","DOIUrl":null,"url":null,"abstract":"In order to achieve the cooperative attack of multi-UAV on targets (including static targets and moving targets), the process is divided into two stages, i.e. cruise stage and strike stage; the motion model of multi-UAV and targets and the observation model of targets are established based on the two-dimensional plane simplification assumption. In the cruise phase, multi-UAV cooperative target state estimation is realized based on Unscented Kalman filter (UKF), and cooperative attack guidance law is established under multiple constraints (including time, attack angle, seeker field angle, etc.) at the strike stage. In this paper, the system simulation is carried out for stationary target and moving target respectively, and the effectiveness of the proposed algorithm and scheme is verified. The results show that the Multi-UAV bearing-only state estimation can converge rapidly, the target positioning accuracy is about 10 m, and the estimation accuracy of the target line of sight angle is about 0.1°; the multi constraint guidance law can effectively improve the cooperative combat performance of the UAV cluster, the time cooperative accuracy is about 0.3s, the attack angle cooperative accuracy is about 0.5°, and the miss distance is less than 1m.","PeriodicalId":325195,"journal":{"name":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on Target State Estimation and Terminal Guidance Algorithm in the Process of Multi-UAV Cooperative Attack\",\"authors\":\"Zhongnan Tang, Yujie Wang, Qing-yang Chen, Xixiang Yang\",\"doi\":\"10.1109/CACRE50138.2020.9229963\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to achieve the cooperative attack of multi-UAV on targets (including static targets and moving targets), the process is divided into two stages, i.e. cruise stage and strike stage; the motion model of multi-UAV and targets and the observation model of targets are established based on the two-dimensional plane simplification assumption. In the cruise phase, multi-UAV cooperative target state estimation is realized based on Unscented Kalman filter (UKF), and cooperative attack guidance law is established under multiple constraints (including time, attack angle, seeker field angle, etc.) at the strike stage. In this paper, the system simulation is carried out for stationary target and moving target respectively, and the effectiveness of the proposed algorithm and scheme is verified. The results show that the Multi-UAV bearing-only state estimation can converge rapidly, the target positioning accuracy is about 10 m, and the estimation accuracy of the target line of sight angle is about 0.1°; the multi constraint guidance law can effectively improve the cooperative combat performance of the UAV cluster, the time cooperative accuracy is about 0.3s, the attack angle cooperative accuracy is about 0.5°, and the miss distance is less than 1m.\",\"PeriodicalId\":325195,\"journal\":{\"name\":\"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CACRE50138.2020.9229963\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CACRE50138.2020.9229963","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Target State Estimation and Terminal Guidance Algorithm in the Process of Multi-UAV Cooperative Attack
In order to achieve the cooperative attack of multi-UAV on targets (including static targets and moving targets), the process is divided into two stages, i.e. cruise stage and strike stage; the motion model of multi-UAV and targets and the observation model of targets are established based on the two-dimensional plane simplification assumption. In the cruise phase, multi-UAV cooperative target state estimation is realized based on Unscented Kalman filter (UKF), and cooperative attack guidance law is established under multiple constraints (including time, attack angle, seeker field angle, etc.) at the strike stage. In this paper, the system simulation is carried out for stationary target and moving target respectively, and the effectiveness of the proposed algorithm and scheme is verified. The results show that the Multi-UAV bearing-only state estimation can converge rapidly, the target positioning accuracy is about 10 m, and the estimation accuracy of the target line of sight angle is about 0.1°; the multi constraint guidance law can effectively improve the cooperative combat performance of the UAV cluster, the time cooperative accuracy is about 0.3s, the attack angle cooperative accuracy is about 0.5°, and the miss distance is less than 1m.