Have a personal or library account? Click to login
Design of Distributed Fusion Predictor and Filter without Feedback for Nonlinear System with Correlated Noises and Random Parameter Matrices Cover

Design of Distributed Fusion Predictor and Filter without Feedback for Nonlinear System with Correlated Noises and Random Parameter Matrices

Open Access
|Jan 2022

References

  1. [1] Scheel, A., Knill, C, Reuter, S., Dietmayer, K. (2016). Multi-sensor multi-object tracking of vehicles using high-resolution radars. In IEEE Intelligent Vehicles Symposium (IV). IEEE, 558-565.10.1109/IVS.2016.7535442
  2. [2] Jing, Z., Pan, H., Li, Y., Dong, P. (2018). Target tracking and multi-sensor fusion with adaptive cubature information filter. In Non-Cooperative Target Tracking, Fusion and Control. Springer, 41-70.10.1007/978-3-319-90716-1_4
  3. [3] Tao, X., Shi, Z., Li, X. (2018). A new intelliSense strategy based on artificial immune system for multirobot cooperation. Journal of Robotics & Mechatronics, 30 (1), 128-137.10.20965/jrm.2018.p0128
  4. [4] Zhang, Y.Y., Huang, Y., Liu, Y., Liu, C.X., Liu, P., Zhang, Y. (2020). Human grasp feature learning and object recognition based on multi-sensor information fusion. Robot, 42 (3), 267-277.
  5. [5] Zhang, Q.Y., Zhang, T., Zhao, Z.Y. (2019). Human motion modes recognition based on multi-sensors. Transducer and Microsystem Technologies, 38 (2), 73-76.
  6. [6] He, F., Shi, Y.F., Wang, F., Zhao, H.W., Qin, H.B. (2018). Research on GMAW welding process pattern recognition based on multi-sensor and support vector machine. Technology Innovation and Application, 34, 1-7.
  7. [7] Carlson, N.A., Neily, C.M. (1987). Distributed Kalman filter architectures. Final report, AFWAL-TR-87-118 1, Avionics Laboratory, WPAFB, Ohio, US.
  8. [8] Carlson, N.A. (1990). Federated square root filter for decentralized parallel processes. IEEE Transactions on Aerospace and Electronic Systems, 26 (3), 517-525.10.1109/7.106130
  9. [9] Carlson, N.A. (1988). Federated filter for fault-tolerant integrated navigation systems. In IEEE Symposium on Position Location and Navigation (PLANS). IEEE, 110-119.10.1109/PLANS.1988.195473
  10. [10] Deng, Z.L. (2012). Information Fusion Estimation Theory and Its Application. Beijing, China: Science Press.
  11. [11] Deng, Z.L., Gao, Y., Mao, L., Li, Y., Hao, G. (2005). New approach to information fusion steady-state Kalman filtering. Automatica, 41 (10), 1695-1707.10.1016/j.automatica.2005.04.020
  12. [12] Sun, S.L. (2004). Multi-sensor information fusion white noise filter weighted by scalars based on Kalman predictor. Automatica, 40 (8), 1447-1453.10.1016/j.automatica.2004.03.012
  13. [13] Julier, S.J., Uhlmann, J.K. (1997). A non-divergent estimation algorithm in the presence of unknown correlations. In American Control Conference (ACC). IEEE, Vol. 4, 2369-2373.10.1109/ACC.1997.609105
  14. [14] Deng, Z., Peng, Z., Qi, W., Liu, J., Yuan, G. (2012). Sequential covariance intersection fusion Kalman filter. Information Sciences, 189, 293-309.10.1016/j.ins.2011.11.038
  15. [15] Yuan, Y.X., Sun, W. (1997). Optimization Theory and Methods. Beijing, China: Science Press.
  16. [16] Cong, J., Li, Y., Qi, G., Sheng, A. (2016). An order insensitive sequential fast covariance intersection fusion algorithm. In Information Sciences, 367, 28-40.10.1016/j.ins.2016.06.001
  17. [17] Lin, H., Sun, S. (2019). Globally optimal sequential and distributed fusion state estimation for multi-sensor systems with cross-correlated noises. Automatica, 101, 128-137.10.1016/j.automatica.2018.11.043
  18. [18] Sun, S. (2020). Distributed optimal linear fusion predictors and filters for systems with random parameter matrices and correlated noises. IEEE Transactions on Signal Processing, 68, 1064-1074.10.1109/TSP.2020.2967180
Language: English
Page range: 17 - 31
Submitted on: Sep 13, 2021
|
Accepted on: Nov 30, 2021
|
Published on: Jan 21, 2022
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2022 Man-lu Liu, Rui Lin, Jian-wen Huo, Li-guo Tan, Qing Ling, Eugene Yuryevich Zybin, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.