Abstract
In order to provide accurate UAV state estimation information for UAV monitoring and control, the UAV state estimation method based on variable structure multi model is studied. Firstly, the state model set is established for the motion forms of UAV, such as smooth flight, lateral turning maneuver and longitudinal jumping maneuver, and the measurement model is established based on the radar measurement principle; Then, based on the variable structure multi model framework, a model set adaptive strategy is proposed, which can solve the problems of too many threshold parameters and complex adaptive strategy; Finally, the simulation scenarios of two radar tracking UAVs are built, and the superiority of the proposed method in the accuracy of state estimation is verified by mathematical simulation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang, Y., Wang, X., Cui, N.: Hybrid consensus-based distributed pseudomeasurement information filter for small UAVs tracking in wireless sensor network. IET Radar Sonar Navig. 14(4), 556–563 (2020)
Huang, J., Zhang, H., Tang, G., et al.: Radar tracking for hypersonic glide vehicle based on aerodynamic model. In: 2017 29th Chinese Control and Decision Conference (CCDC), Chongqing, China, pp. 1080–1084 (2017)
Kim, J., Vaddi, S.S., Menon, P.K., et al.: Comparison between nonlinear filtering techniques for spiraling ballistic missile state estimation. IEEE Trans. Aerosp. Electron. Syst. 48(1), 313–328 (2012)
Zhang, K., Xiong, J., Han, C., Lan, X.: A tracking algorithm of hypersonic glide reentry vehicle via aerodynamic model. J. Astronaut. 38(02), 123–130 (2017)
Zhang, K., Xiong, J., Fu, T., et al.: Aerodynamic parameter modeling of hypersonic gliding missile for adaptive tracking. J. Natl. Univ. Def. Technol. 041(001), 101–107 (2019)
Lu, Z., Cai, Y., He, J., et al.: A tracking algorithm for near-space hypersonic vehicles based on aerodynamic acceleration model. In: Chinese Association of Automation, Wuhan, China, pp. 381–388 (2017)
He, S., Wu, P., et al.: A tracking algorithm for near space hypersonic reentry glide target. J. Astronaut. 41(05), 553–559 (2020)
Zhou, H.: A “Current” statistical model and adaptive tracking algorithm for maneuvering targets. Acta Aeronautica et Astronautica Sinica 4(1), 73–86 (1983)
Wang, G., Li, J., Zhang, X., et al.: A tracking model for near space hypersonic slippage leap maneuvering target. Acta Aeronautica et Astronautica Sinica 36(7), 2400–2410 (2015)
Singer, R.A.: Estimating optimal tracking filter performance for manned maneuvering targets. IEEE Trans. Aerosp. Electron. Syst. 6(4), 473–483 (1970)
Cheng, Y., Tang, S., Lyu, S., et al.: Aerodynamic statistics-based trajectory estimation of hypersonic maneuvering target. IEEE Access 8, 227642–227656 (2020)
Li, F., Xiong, J., Qu, Z., et al.: A damped oscillation model for tracking near space hypersonic gliding targets. IEEE Trans. Aerosp. Electron. Syst. 55(6), 2871–2890 (2019)
Huang, J., Li, Y., Tang, G., et al.: Adaptive tracking method for hypersonic glide target. Acta Aeronautica et Astronautica Sinica 41(9), 323786 (2020)
Shan, F., Tan, Q., Li, Q., et al.: Trajectory tracking for hypersonic glide vehicles based on improved sine-AIMM. In: Chinese Control Conference, Dalian, China, pp. 5475–5480 (2017)
Zhang, X., Wang, G., et al.: Tracking of hypersonic boost-to-glide trajectory target in near-space. J. Astronaut. 36(10), 1125–1132 (2015)
Tugnait, J.K.: Adaptive estimation and identification for discrete systems with markov jump parameters. IEEE Trans. Autom. Control 27(5), 1054–1065 (1981)
Ackerson, G., Fu, K.: On state estimation in switching environments. IEEE Trans. Autom. Control 15(1), 10–17 (1970)
Blom, H.A.P., Bar-Shalom, Y.: The interacting multiple model algorithm for systems with Markovian switching coefficients. IEEE Trans. Autom. Control 33(8), 780–783 (1988)
Hernandez, M., Farina, A.: PCRB and IMM for target tracking in the presence of specular multipath. IEEE Trans. Aerosp. Electron. Syst. 56(3), 2437–2449 (2020)
Nadarajah, N., Tharmarasa, R., Mcdonald, M., et al.: IMM forward filtering and backward smoothing for maneuvering target tracking. IEEE Trans. Aerosp. Electron. Syst. 48(3), 2673–2678 (2012)
Ho, T.J.: A switched IMM-Extended Viterbi estimator-based algorithm for maneuvering target tracking. Automatica 47(1), 92–98 (2011)
Li, X.R., Zhi, X., Zhang, Y.: Design and evaluation of a model-group switching algorithm for multiple-model estimation with variable structure. IEEE Trans. Autom. Control 45(11), 2047–2060 (2002)
Li, X.R.: Multiple-model estimation with variable structure-Part II: model-set adaptation. IEEE Trans. Autom. Control 45(11), 2047–2060 (2000)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Chen, J., Wang, Y., Chen, S., Lu, W., Ma, C. (2022). Research on UAV State Estimation Method Based on Variable Structure Multiple Model. In: Fan, W., Zhang, L., Li, N., Song, X. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2022. Communications in Computer and Information Science, vol 1712. Springer, Singapore. https://doi.org/10.1007/978-981-19-9198-1_24
Download citation
DOI: https://doi.org/10.1007/978-981-19-9198-1_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-9197-4
Online ISBN: 978-981-19-9198-1
eBook Packages: Computer ScienceComputer Science (R0)