ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Aerodynamic coefficient identification method based on noise statistics estimation
Received date: 2024-07-09
Revised date: 2024-07-29
Accepted date: 2024-09-24
Online published: 2024-10-23
Supported by
National Level Project
Using flight data to verify and update the wind-tunnel aerodynamic database is an important part of flight vehicle design and evaluation program. In response to the lack of angular acceleration measurement in flight tests， a novel aerodynamic coefficient identification method has been developed in this paper. Firstly， a mathematical model of aerodynamic coefficient identification was constructed by modeling the derivatives of aerodynamic coefficient respect to time as first-order Gauss-Markov process. Then， analytical expressions for the unknown statistics， such as the covariances of process and measurement noise， were derived theoretically by maximizing the likelihood function. The state estimation was conducted by using the Square Root Unscented Kalman Filter （SRUKF） associated with the Unscented Rauch-Tung-Striebel Smoother （URTSS）. The unknown statistics were computed explicitly and updated iteratively， based on the state estimation results. Thereby， the time histories of aerodynamic coefficients， as the augmented state variables， were obtained. The effectiveness of the developed method was demonstrated by two examples of aircraft aerodynamic coefficient identification. The results showed that the unknown statistics and aerodynamic coefficients were estimated accurately. In addition， the method is of robust convergence with respect to the initial estimates of unknown statistics.
Qing WANG , Fengqi ZHENG , Di DING , Xi YUE . Aerodynamic coefficient identification method based on noise statistics estimation[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2025 , 46(7) : 130920 -130920 . DOI: 10.7527/S1000-6893.2024.30920
| 1 | HAMEL P G， JATEGAONKAR R V. Evolution of flight vehicle system identification?［J］. Journal of Aircraft， 1996， 33（1）： 9-28. |
| 2 | GREENBERG H. A survey of methods for determining stability parameters of an airplane from dynamic flight measurements： NACA TN-2340?［R］. Washington， D.C.： NASA， 1951. |
| 3 | MAINE R E， ILIFF K W. Application of parameter estimation to aircraft stability and control， the output error approach： NASA RP-1168?［R］. Washington， D.C.： NASA， 1986. |
| 4 | MAINE R E， ILIFF K W. Formulation and implementation of a practical algorithm for parameter estimation with process and measurement noise?［C］?∥6th Atmospheric Flight Mechanics Conference. Reston： AIAA， 1980. |
| 5 | JATEGAONKAR R V， PLAETSCHKE E. Identification of moderately nonlinear flight mechanics systems with additive process and measurement noise［J］. Journal of Guidance， Control， and Dynamics， 1990， 13（2）： 277-285. |
| 6 | GRAUER J A， MORELLI E A. A new formulation of the filter-error method for aerodynamic parameter estimation in turbulence?［C］?∥Proceedings of the AIAA Atmospheric Flight Mechanics Conference. Reston： AIAA， 2015. |
| 7 | WANG Q， ZHENG F Q， QIAN W Q， et al. A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence［J］. Chinese Journal of Aeronautics， 2023， 36（2）： 17-28. |
| 8 | MORELLI E. Practical aspects of the equation-error method for aircraft parameter estimation［C］?∥AIAA Atmospheric Flight Mechanics Conference and Exhibit. Reston： AIAA， 2006. |
| 9 | DE VISSER C C， POOL D M. Stalls and splines： Current trends in flight testing and aerodynamic model identification?［J］. Journal of Aircraft， 2023， 60（5）： 1480-1502. |
| 10 | MOKHTARI M A， SABZEHPARVAR M. Identification of spin maneuver aerodynamic nonlinear model by applying ensemble empirical mode decomposition and extended multipoint modeling［J］. Proceedings of the Institution of Mechanical Engineers， Part G： Journal of Aerospace Engineering， 2019， 233（5）： 1865-1878. |
| 11 | OVCHARENKO V N， POPLAVSKY B K. Identification of nonstationary aerodynamic characteristics of an aircraft based on flight data?［J］. Journal of Computer and Systems Sciences International， 2021， 60（6）： 864-874. |
| 12 | LI J S， ZHUANG L， SONG J H， et al. An aerodynamic model identification method suitable for low-quality flight data［C］∥2020 3rd International Conference on Unmanned Systems （ICUS）. Piscataway： IEEE， 2020： 381-388. |
| 13 | 颜楚雄， 童轶男， 宋加洪， 等. 基于贝叶斯估计理论的再入飞行器气动辨识方法［J］. 中国科学： 物理学力学天文学， 2021， 51（10）： 104705. |
| Yan C X， TONG Y N， SONG J H， et al. Aerodynamic identification method of maneuverable vehicles based on the Bayes estimation theorem?［J］. Scientia Sinica Physica， Mechanica & Astronomica， 2021， 51（10）： 104705 （in Chinese）. | |
| 14 | STALFORD H L. High-alpha aerodynamic model identification of T-2C aircraft using the EBM method［J］. Journal of Aircraft， 1981， 18（10）： 801-809. |
| 15 | 王启， 简政， 张培田， 等. 利用大迎角试飞数据辨识飞机气动导数［J］. 飞行力学， 2005， 23（1）： 68-72. |
| WANG Q， JIAN Z， ZHANG P T， et al. Aircraft aer-odynamic parameter identification by using HAOA flight test data［J］. Flight Dynamics， 2005， 23（1）： 68-72 （in Chinese）. | |
| 16 | 臧剑文， 毕晓烨， 金钊， 等. 基于迎角分区的全局飞行器气动参数辨识方法［J］. 系统工程与电子技术， 2022， 45（11）： 3588-3596. |
| ZANG J W， BI X Y， JIN Z， et al. Global aircraft aerodynamic parameter identification method based on angle of attack partitioning?［J］. Systems Engineering and Electronic， 2022， 45（11）： 3588-3596 （in Chinese）. | |
| 17 | DAS S， KUTTIERI R A， SINHA M， et al. Neural partial differential method for extracting aerodynamic derivatives from flight data?［J］. Journal of Guidance， Control， and Dynamics， 2010， 33（2）： 376-384. |
| 18 | WANG Q， WU K Y， ZHANG T J， et al. Aerodynamic modeling and parameter estimation from QAR data of an airplane approaching a high-altitude airport［J］. Chinese Journal of Aeronautics， 2012， 25（3）： 361-371. |
| 19 | SINGH S， GHOSH A. Parameter estimation from flight data of a missile using maximum likelihood and neural network method?［C］?∥AIAA Atmospheric Flight Mechanics Conference and Exhibit. Reston： AIAA， 2006. |
| 20 | TONDJI Y， GHAZI G， BOTEZ R M. CRJ 700 longitudinal aerodynamic coefficients identification using support vector machine?［C］?∥AIAA Aviation 2023 Forum. Reston： AIAA， 2023. |
| 21 | 蔡金狮， 汪清， 王文正， 等. 飞行器系统辨识学［M］. 北京： 国防工业出版社， 2003： 293-296. |
| CAI J S， WANG Q， WANG W Z， et al. System identification of aircraft［M］. Beijing： National Defense Industry Press， 2003： 293-296 （in Chinese）. | |
| 22 | KLEIN V， MORELLI E A. Aircraft system identification-Theory and practice［M］. Reston： AIAA， 2006： 367-369. |
| 23 | MORELLI E A. Estimating noise characteristics from flight test data using optimal Fourier smoothing［J］. Journal of Aircraft， 1995， 32（4）： 689-695. |
| 24 | HOFF J C. Fortran programs for aircraft parameter identification using the estimation-before-modelling technique： College of Aeronautics Report No. 9709［R］. Cranfield， Bedford： Cranfield University， 1997. |
| 25 | SARKAR A， PANNEERSELVAM S， SUNDARRAJAN R. Aerodynamic coefficients estimation of different flight vehicles under limited measurements［C］?∥24th Atmospheric Flight Mechanics Conference. Reston： AIAA， 1999. |
| 26 | VAN DER MERWE R， WAN E A. The square-root unscented Kalman filter for state and parameter-estimation［C］∥2001 IEEE International Conference on Acoustics， Speech， and Signal Processing. Proceedings （Cat. No.01CH37221）. Piscataway： IEEE， 2001： 3461-3464. |
| 27 | BRUNKE S， CAMPBELL M E. Square root sigma point filtering for real-time， nonlinear estimation?［J］. Journal of Guidance， Control， and Dynamics， 2004， 27（2）： 314-317. |
| 28 | GEERAERT J L， MCMAHON J W. Square-root unscented Schmidt-Kalman filter［J］. Journal of Guidance， Control， and Dynamics， 2017， 41（1）： 280-287. |
| 29 | S?RKK? S. Unscented Rauch-Tung-Striebel smoother［J］. IEEE Transactions on Automatic Control， 2008， 53（3）： 845-849. |
| 30 | GARCIA-VELO J， WALKER B K. Aerodynamic parameter estimation for high-performance aircraft using extended Kalman filtering［J］. Journal of Guidance， Control， and Dynamics， 1997， 20（6）： 1257-1260. |
| 31 | CHOWDHARY G， JATEGAONKAR R. Aerodynamic parameter estimation from flight data applying extended and unscented Kalman filter?［C］?∥AIAA Atmospheric Flight Mechanics Conference and Exhibit. Reston： AIAA， 2006. |
| 32 | JULIER S， UHLMANN J， DURRANT-WHYTE H F. A new method for the nonlinear transformation of means and covariances in filters and estimators［J］. IEEE Transactions on Automatic Control， 2000， 45（3）： 477-482. |
| 33 | JULIER S J， UHLMANN J K. Unscented filtering and nonlinear estimation［J］. Proceedings of the IEEE， 2004， 92（3）： 401-422. |
| 34 | MORELLI E A. Flight test maneuvers for efficient aerodynamic modeling［J］. Journal of Aircraft， 2012， 49（6）： 1857-1867. |
| 35 | GRESHAM J L， SIMMONS B M， FAHMI J M W， et al. Remote uncorrelated pilot input excitation assessment for unmanned aircraft aerodynamic modeling［J］. Journal of Aircraft， 2023， 60（3）： 955-967. |
| 36 | JATEGAONKAR R V. Flight vehicle system identification： A time domain methodology［M］. Reston： AIAA， 2006： 167-171， 207-215， 257-259. |
| 37 | YOKOYAMA N. Parameter estimation of aircraft dynamics via unscented smoother with expectation-maximization algorithm?［J］. Journal of Guidance， Control， and Dynamics， 2011， 34（2）： 426-436. |
| 38 | LIU Y Y， WANG H W， ZHANG W. Robust parameter estimation with outlier-contaminated correlated measurements and applications to aerodynamic coefficient identification?［J］. Aerospace Science and Technology， 2021， 118： 106995. |
/
| 〈 |
|
〉 |
CJA