{"title":"小型固定翼无人机风估计的不变扩展卡尔曼滤波","authors":"Zakia Ahmed;Craig A. Woolsey","doi":"10.1109/TCST.2025.3564884","DOIUrl":null,"url":null,"abstract":"This article presents the design and implementation of an invariant extended Kalman filter (EKF) for wind estimation using a small, fixed-wing uncrewed aerial vehicle (UAV). First, it is shown that the UAV’s dynamics, extended to include a trivial model for the wind velocity dynamics, are invariant with respect to the Lie group <inline-formula> <tex-math>$\\text {SE}(3)$ </tex-math></inline-formula>, the special Euclidean group of rigid transformations. It is also shown that an output comprising the vehicle’s inertial state and airspeed is equivariant with respect to <inline-formula> <tex-math>$\\text {SE}(3)$ </tex-math></inline-formula>. Based on these analysis results, an invariant EKF is then designed for the extended state equations and is implemented on experimental flight data. Wind estimates from the invariant EKF are compared with estimates obtained using a conventional EKF for two nominal aircraft motions: constant altitude, wings level flight, and constant altitude turning flight. The obtained wind estimates are then compared with wind measurements reconstructed using data from the aircraft’s air data unit comprising an angle of attack (AoA) flow vane, flank angle flow vane, and Kiel probe. The experimental results corroborate the expectation that the invariant EKF outperforms a conventional EKF in wind estimation accuracy.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 5","pages":"1799-1809"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Invariant Extended Kalman Filter for Wind Estimation Using a Small, Fixed-Wing Uncrewed Aerial Vehicle\",\"authors\":\"Zakia Ahmed;Craig A. Woolsey\",\"doi\":\"10.1109/TCST.2025.3564884\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents the design and implementation of an invariant extended Kalman filter (EKF) for wind estimation using a small, fixed-wing uncrewed aerial vehicle (UAV). First, it is shown that the UAV’s dynamics, extended to include a trivial model for the wind velocity dynamics, are invariant with respect to the Lie group <inline-formula> <tex-math>$\\\\text {SE}(3)$ </tex-math></inline-formula>, the special Euclidean group of rigid transformations. It is also shown that an output comprising the vehicle’s inertial state and airspeed is equivariant with respect to <inline-formula> <tex-math>$\\\\text {SE}(3)$ </tex-math></inline-formula>. Based on these analysis results, an invariant EKF is then designed for the extended state equations and is implemented on experimental flight data. Wind estimates from the invariant EKF are compared with estimates obtained using a conventional EKF for two nominal aircraft motions: constant altitude, wings level flight, and constant altitude turning flight. The obtained wind estimates are then compared with wind measurements reconstructed using data from the aircraft’s air data unit comprising an angle of attack (AoA) flow vane, flank angle flow vane, and Kiel probe. The experimental results corroborate the expectation that the invariant EKF outperforms a conventional EKF in wind estimation accuracy.\",\"PeriodicalId\":13103,\"journal\":{\"name\":\"IEEE Transactions on Control Systems Technology\",\"volume\":\"33 5\",\"pages\":\"1799-1809\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Control Systems Technology\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11006968/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Control Systems Technology","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11006968/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
An Invariant Extended Kalman Filter for Wind Estimation Using a Small, Fixed-Wing Uncrewed Aerial Vehicle
This article presents the design and implementation of an invariant extended Kalman filter (EKF) for wind estimation using a small, fixed-wing uncrewed aerial vehicle (UAV). First, it is shown that the UAV’s dynamics, extended to include a trivial model for the wind velocity dynamics, are invariant with respect to the Lie group $\text {SE}(3)$ , the special Euclidean group of rigid transformations. It is also shown that an output comprising the vehicle’s inertial state and airspeed is equivariant with respect to $\text {SE}(3)$ . Based on these analysis results, an invariant EKF is then designed for the extended state equations and is implemented on experimental flight data. Wind estimates from the invariant EKF are compared with estimates obtained using a conventional EKF for two nominal aircraft motions: constant altitude, wings level flight, and constant altitude turning flight. The obtained wind estimates are then compared with wind measurements reconstructed using data from the aircraft’s air data unit comprising an angle of attack (AoA) flow vane, flank angle flow vane, and Kiel probe. The experimental results corroborate the expectation that the invariant EKF outperforms a conventional EKF in wind estimation accuracy.
期刊介绍:
The IEEE Transactions on Control Systems Technology publishes high quality technical papers on technological advances in control engineering. The word technology is from the Greek technologia. The modern meaning is a scientific method to achieve a practical purpose. Control Systems Technology includes all aspects of control engineering needed to implement practical control systems, from analysis and design, through simulation and hardware. A primary purpose of the IEEE Transactions on Control Systems Technology is to have an archival publication which will bridge the gap between theory and practice. Papers are published in the IEEE Transactions on Control System Technology which disclose significant new knowledge, exploratory developments, or practical applications in all aspects of technology needed to implement control systems, from analysis and design through simulation, and hardware.