Volume 12, Issue 4 (Journal of Control, V.12, N.4 Winter 2019)                   JoC 2019, 12(4): 15-22 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Hosseini S N, Haeri M, Khaloozadeh H. Joint State Estimation and System Classification Using Particle Filtering and Interacting Multiple-Model for Maneuvering Target Tracking. JoC 2019; 12 (4) :15-22
URL: http://joc.kntu.ac.ir/article-1-515-en.html
1- Scince and research Branch, Azad U
2- Sharif U. of T.
3- KNTU University
Abstract:   (6680 Views)
In this paper, the problem of joint tracking and system calcification for a maneuvering target has been investigated. The system classification could improve performance of a tracking algorithm in a majority of applications. For instance, it is very crucial to determine the class of target in caring systems like air traffic control, marine care, and air defense at any time. In contrast to the existing solutions, which consider a separate filter for each class, we propose a single particle filter to estimate the class of target leading to a considerable reduction in computation complexity. Simulation results show that the proposed algorithm can estimate the class of target efficiently
Full-Text [PDF 639 kb]   (2739 Downloads)    
Type of Article: Research paper | Subject: Special
Received: 2017/08/11 | Accepted: 2018/07/7 | Published: 2019/05/4

References
1. [1] حمید خالوزاده، عطیه کشاورز محمدیان، "مروری بر کاربردهای نظریه تخمین، شناسایی و کنترل تصادفی در سیستم‌های صنعتی"، مجله کنترل، جلد 8، شماره 3، پاییز 1393.
2. [2] H. Khaloozadeh, A. Karsaz, "Modified input estimation technique for tracking maneuvering targets," IET Radar Sonar & Navigation, vol. 3, pp. 30-41, 2008. [DOI:10.1049/iet-rsn:20080028]
3. [3] H. Rahmati, H. Khaloozadeh, M. Ayati, "Novel approach for nonlinear maneuvering target tracking based on input estimation, "Applied Mechanics and Materials, pp.4415-4423, 2012. [DOI:10.4028/www.scientific.net/AMM.110-116.4415]
4. [4] G.W. Pulford, "A survey of Maneuvering target tracking methods," IEEE Transactions on Aerospace and Electronic Systems, vol. 27, no. 1, 2015.
5. [5] X.R. Li, "Multiple model bootstrap filter for maneuvering," IEEE Transactions on Aerospace and Electronic Systems, vol. 36, no. 3, pp. 1006-1012, 2000. [DOI:10.1109/7.869522]
6. [6] G.W. Pulford, S. Challa, "Joint target tracking and classification using radar and ESM sensors," IEEE Transactions on Aerospace and Electronic Systems, vol. 37, no. 3, pp. 1039-1055, 2001. [DOI:10.1109/7.953266]
7. [7] A. Averbuch, E. Mazor, Y. Bar-shalom, J. Dayan, "Interacting multiple model methods in target tracking: A Survey," IEEE Transactions on Aerospace and Electronic Systems, vol. 34, no. 3, pp. 103-123, 1998. [DOI:10.1109/7.640267]
8. [8] X. Chen, J. Gao, X. Han, "An algorithm based on interacting multiple models for maneuvering target tracking," IEEE Conference on Decision and Control, vol. 2, pp. 405-408, 2014. [DOI:10.1109/ITAIC.2014.7065080]
9. [9] A. Abdul Salam, "Adaptive tracking of maneuvering target using two-stage Kalman filter," IEEE International Symposium on Processing and Information Technology, 749-754, 2015. [DOI:10.1109/ISSPIT.2015.7394423]
10. [10] X. FU, Y. Shang, H. Yuan, "Improved diagonal interacting multiple model algorithm for maneuvering target tracking based on H∞ filter," IET Control Theory & Application, vol. 9, pp. 1887-1892, 2015. [DOI:10.1049/iet-cta.2014.0685]
11. [11] L. Hun, A. Xie, Z. Ren, D.S. Bernstein, "Maneuvering target tracking with unknown acceleration using retrospective-cost-based adaptive input and state estimation," 34th Chinese Control Conference, Hangzhou, China, 2015.
12. [12] W. Yanxuan, C. Jianbin, "An adaptive maneuvering target tracking algorithm based on three-dimensional parameter identification model," 34th Chinese Control Conference, Hangzhou, China, pp. 5479-5483, 2015. [DOI:10.1109/ChiCC.2015.7260496]
13. [13] K. Zhan, L. Xu, H. Jiang, "Joint tracking and classification with constraints and reassignment by radar and ESM," Digital Signal Process, 2014.
14. [14] H. Yihui, X. Wei, P. Hui, C. Xiliang, L. Jun, "A method of taracking maneuver target," 27th Chinese Control and Decision Conference, pp. 2004-2008, 2015. [DOI:10.1109/CCDC.2015.7162250]
15. [15] S. Ranhnama, M.R. Arvan, "Comparison of extended and unscented Kalman smoother in deriving kinematic characteristics of a high maneuver flying target" International Conference on Modelling, Identification and Control, Shanghai, China, pp. 537-542, 2011. [DOI:10.1109/ICMIC.2011.5973762]
16. [16] P. Smets, B. Ristic, "Kalman filter and joint tracking and classification based on belief functions in the TBM Framework," IEEE Conference on Decision and control, 2678-2685, 2005.
17. [17] W. Mei, G.L. Shan, X. Rongli, "An efficient bayesian algorithm for joint target tracking and classification," American Control Conference, pp. 2090-2098, 2005.
18. [18] L. Zhu, X. Cheng, "High maneuver target tracking in coordinated turns," IET Radar, Sonar & Navigation, vol. 9, pp. 1078-1087, 2015. [DOI:10.1049/iet-rsn.2014.0533]
19. [19] K. Zhan, L. Xu, H. Jiang, "An improved mixture unscented Kalman filters algorithm of joint target tracking and classification," IEEE Chinese Guidance & Navigation and Control Conference, Yantai, China, pp. 1197-1202, 2014. [DOI:10.1109/CGNCC.2014.7007372]
20. [20] M. Melzi, A. Ouldali, "Joint multiple target tracking and classification using the unscented Kalman particle PHD filter," American Control Conference, pp. 534-537, 2011. [DOI:10.1109/NEWCAS.2011.5981202]
21. [21] D. Angelova, L. Mihaylova, "Joint target tracking and classification with particle filtering and mixture Kalman filtering using kinematic radar information," Elsevier, Digital Signal Processing, vol. 16, pp. 180-204, 2006. [DOI:10.1016/j.dsp.2005.04.007]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Journal of Control

Designed & Developed by : Yektaweb