|3/2016 - 9|
A Novel Target Tracking Algorithm for Simultaneous Measurements of Radar and Infrared SensorsGHAZAL, M. , DOUSTMOHAMMADI, A.
|Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (1,169 KB) | Citation | Downloads: 292 | Views: 1,118|
infrared sensors, radar tracking, state estimation, filtering algorithms, minimax techniques
tracking(11), transaction(7), radar(6), estimation(6), control(6), systems(5), system(5), signal(5), sensors(5), processing(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 57 - 64
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03009
Web of Science Accession Number: 000384750000009
SCOPUS ID: 84991107981
In this paper, a game theory filtering technique is proposed to track a maneuvering target using radar/infrared (IR) sensors. It is shown that use of game theory technique can improve filter performance in presence of model uncertainties, measurement noise, and unknown steering command of the target. The tracking problem of maneuvering target is formulated as a zero-sum dynamic game and a utility function is developed to find equilibrium point of this game in a deterministic fashion to estimate target characteristics, including its position and velocity. To improve the filter performance, a proposed linear matrix inequality is implemented to obtain the introduced parameter in utility function. The robustness of the filter is guaranteed by minimizing the utility function for the worst case region of the measurement noise and steering command. Simulation results illustrate the improved performance of the proposed filter compared to extended Kalman and cubature Kalman filters.
|References|||||Cited By «-- Click to see who has cited this paper|
| P. Wu, X. Li, J. Kong, J. Liu, "Heterogeneous Multiple Sensors Joint Tracking of Maneuvering Target in Clutter," Sensors, vol. 15, no. 7, pp. 17350-17365, 2015. |
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 9]
 P. Jing, S. Xu, Z. Chen, "A Novel State Transition and Data Association Scheme Suitable For Asynchronous Radar and Infrared Sensors," IEEE China Summit & International Conference on Signal and Information Processing, Xi'an, China, 2014, pp. 768-771.
[CrossRef] [SCOPUS Times Cited 1]
 J. Yin, B. Cui, Y. Wang, "A Novel Maneuvering Target Tracking Algorithm for Radar/Infrared Sensors," Chinese Journal of Electronics, vol. 19, no. 4, pp. 752-756, 2010.
 Z. Zhu, "Shipborne Radar Maneuvering Target Tracking Based on The Variable Structure Adaptive Grid Interacting Multiple Model," Journal of Zhejiang University Science C, vol. 14, no. 9, pp. 733-742, 2013.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 5]
 W. Qingchao, W. Wenfei, "Tracking Method Based on Separation and Combination of the Measurements for Radar and IR Fusion System," Journal of System Engineering and Electronics, vol. 20, no. 2, pp. 241-246, 2009.
 P. Wu, L. Xingxiu, Z. Lianzheng, B. Yuming, "Tracking Algorithm With Radar And Infrared Sensors Using a Novel Adaptive Grid Interacting Multiple Model," IET Science Measurement & Technology, vol. 8, no. 5, pp. 270-276, 2014.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 11]
 M. A. Richards, "Fundamentals of Radar Signal Processing," pp. 37-49, McGraw-Hill Education, USA, 2005.
 Y. J. He, M. Li, J. L. Zhang, J. P. Yao, "Infrared Target Tracking via Weighted Correlation Filter," Infrared Physics & Technology, vol. 73, pp. 103-114, 2015.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 19]
 B. Mocanu, T. Ruxandra, T. Zaharia, "3D Object Metamorphosis with Pseudo Metameshes," Advances in Electrical and Computer Engineering, vol. 15, no. 1, pp. 115-122, 2015.
[CrossRef] [Full Text] [Web of Science Times Cited 17] [SCOPUS Times Cited 15]
 Y. Ulker, B. Gunsel, "Multiple Model Target Tracking with Variable Rate Particle Filters," Digital Signal Processing, vol. 22, no. 3, pp. 417-429, 2012.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 20]
 C. Suliman, C. Cruceru, F. Moldoveanu, "Kalman Filter Based Tracking in an Video Surveillance System," Advances in Electrical and Computer Engineering, vol.10, no. 2, pp. 30-34, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 8] [SCOPUS Times Cited 11]
 A. Houles, Y. Bar-Shalom, "Multisensor Tracking of A Maneuvering Target in Clutter," IEEE Transaction on Aerospace Electronic Systems, vol. 25, no. 2, pp. 176-189, 1989.
[CrossRef] [Web of Science Times Cited 12] [SCOPUS Times Cited 12]
 S. M. Kalami Heris, H. Khaloozadeh, "Ant Colony Estimator: An intelligent particle filter based on ACOR," Engineering Applications of Artificial Intelligence, vol. 28, no. 1, pp. 78-85, 2014.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 9]
 F. Valdez, P. Melin, O. Castillo "An Improved Evolutionary Method With Fuzzy Logic For Combining Particle Swarm Optimization and Genetic Algorithms," Applied Soft Computing, vol. 11, no. 2, pp. 2625-2632, 2011.
[CrossRef] [Web of Science Times Cited 125] [SCOPUS Times Cited 160]
 R. E. Precup, R. David, E. M. Petriu, S. Preitl, M. Radac, "Fuzzy logic-based adaptive gravitational search algorithm for optimal tuning of fuzzy controlled servo systems," IET Control Theory & Applications, vol. 7, no. 1, pp. 99-107, 2013.
[CrossRef] [Web of Science Times Cited 52] [SCOPUS Times Cited 57]
 I. D. Falco, E. Laskowski, R. Olejnik, U. Scafuri, E. Tarantino, M. Tudruj, "Extremal optimization applied to load balancing in execution of distributed programs," Applied Soft Computing, vol. 30, pp. 501-513, 2015.
[CrossRef] [Web of Science Times Cited 15] [SCOPUS Times Cited 24]
 N. Tomin, A. Zhukov, D. Sidorov, V. Kurbatsky, D. Panasetsky, V. Spiryaev, "Random forest based model for preventing large-scale emergencies in power systems," International Journal of Artificial Intelligence, vol. 13, no. 1, pp. 211-228, 2015.
 G. Zames, "Feedback and Optimal Sensitivity: Model Reference Transformations Multiplicative Seminorms, And Approximate Inverses," IEEE Transaction on Automatic Control, vol. 26, no. 2, pp. 301-320, 1981.
[CrossRef] [Web of Science Times Cited 1162] [SCOPUS Times Cited 1409]
 R. D. Martin, V. J. Yohai, R. H. Zamar, "Min-Max Bias Robust Regression," The Annals of Statistics, vol. 17, pp. 1608-1630, 1989.
[CrossRef] [Web of Science Times Cited 82]
 D. Gu, "A Game Theory Approach To Target Tracking in Sensor Networks," IEEE Transaction on System Man and Cybernetics Part B, vol. 41, no. 1, pp. 2-13, 2011.
[CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 47]
 J. C. Preisig, "Optimal Minmax Estimation and The Development of Minmax Estimation Error Bounds," IEEE International Conference on Acoustics, Speech, and Signal Processing, San Francisco, USA, 1992, pp. 285-288.
[CrossRef] [SCOPUS Times Cited 3]
 I. Yaesh, U. Shaked, "Min-Max Kalman filtering," Systems and Control Letters, vol. 53, no. 3, pp. 217-228. 2004.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 11]
 S. Zhuk, V. Mallet, "Reduced Minimax Filtering by Means Of Differential-Algebraic Equations," 5th International Conference on Physics and Control, León, Spain, 2011, pp. 1-8.
 S. Zhuk, "Minimax State Estimation for Linear Stationary Differential-Algebraic Equations," in Proc. 16th IFAC Symposium on System Identification, Brussels, Belgium, 2012, pp. 143-148.
[CrossRef] [SCOPUS Times Cited 12]
 I. Yaesh, U. Shaked, "Discrete-Time Min-Max Tracking," IEEE Transaction on Aerospace Electronic Systems, vol. 42, no. 2, pp. 540-547, 2006.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 7]
 D. Simon, "A Game Theory Approach to Constrained Minimax State Estimation," IEEE Transaction on Signal Processing, vol. 54, no. 2, pp. 405-412, 2006.
[CrossRef] [Web of Science Times Cited 49] [SCOPUS Times Cited 62]
 I. Yaesh, U. Shaked, "Game Theory Approach to Optimal Linear State Estimation and Its Relation To The Minimum H?-Norm Estimation," IEEE Transaction on Automatic Control, vol. 37, no. 6, pp. 828-831, 1992.
[CrossRef] [Web of Science Times Cited 32] [SCOPUS Times Cited 49]
 B. D. O. Anderson, J. B. Moore, "Optimal Filtering," pp. 138-142, Prentice-Hall Englewood Cliffs, New Jersey, USA, 1979.
 I. Arasaratnam, "Cubature Kalman Filters" IEEE Transaction on Automatic Control, vol. 54, no. 6, pp. 1254-1269, 2009.
[CrossRef] [Web of Science Times Cited 911] [SCOPUS Times Cited 1442]
Web of Science® Citations for all references: 2,577 TCR
SCOPUS® Citations for all references: 3,395 TCR
Web of Science® Average Citations per reference: 86 ACR
SCOPUS® Average Citations per reference: 113 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2019-02-15 21:39 in 166 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.