Abstract
In this paper, the problem of bearings-only maneuvering target tracking in sensors network is investigated. Two objectives are proposed and optimized by the ant colony optimization (ACO), then two kinds of node searching strategies of the ACO algorithm are presented. On the basis of the nodes determined by the ACO algorithm, the interacting multiple models extended Kalman filter (IMMEKF) for the multi-sensor bearings-only maneuvering target tracking is introduced. Simulation results indicate that the proposed ACO algorithm performs better than the Closest Nodes method. Furthermore, the Strategy 2 of the two given strategies is preferred in terms of the requirement of real time.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
I. Kadar. Optimum geometry selection for sensors fusion[C]//Proceedings of SPIE — Signal Processing, Sensors Fusion and Target Recognition VII. Orlando, USA: SPIE, 1998: 96–107.
L. M. Kaplan. Node selection for target tracking using bearing measurements from unattended ground sensors[C]//Proceedings of IEEE International Conference on Aerospace Conference. Piscataway, New Jersey: IEEE Press, 2003: 2137–2152.
Q. Le, L. M. Kaplan, J. H. McClellan. Multiple-mode Kalman filtering with node selection using bearings-only measurements[C]//Proceedings of the 36th Southeastern Symposium on System Theory. Piscataway, New Jersey: IEEE Press, 2004: 185–189.
L. M. Kaplan. Transmission range control during autonomous node selection for wireless sensor networks[C]//Proceedings of IEEE International Conference on Aerospace Conference. Piscataway, New Jersey: IEEE Press, 2004, 3: 2072–2087.
M. Dorigo, V. Maniezzo, A. Colorni. The ant system: optimization by a colony of cooperating agents[J]. IEEE Transactions on Systems, Man and Cybernetics, 1996, 26(1): 28–41.
M. G. Ippolito, E. R. Sanseverino, F. Vuinovich. Multiobjective ant colony search algorithm for optimal electrical distribution system strategical planning[C]//Proceedings of IEEE International Conference on Evolutionary Computation. New York: IEEE Press, 2004: 1924–1931.
K. Verbeeck, A. Nowe. Colonies of learning automata[J]. IEEE Transactions on Systems, Man, and Cybernetics — Part B, 2002, 32(6): 772–780.
B. Ristic, M. Sanjeev Arulampalam. Tracking a maneuvering target using angle-only measurements: algorithms and performance[J]. Signal Processing, 2003, 83(6): 1223–1238.
H. A. P Blom, Y. Bar-Shalom. The interacting multiple model algorithm for systems with Markovian switching coefficients[J]. IEEE Transactions on Automatic Control, 1988, 33(8): 780–783.
Author information
Authors and Affiliations
Additional information
This paper was supported by the Natural Science Foundation of Jiangsu province of China (BK2004132).
Benlian XU received the B.S. degree in mechanical engineering from Changsha Communication University, China, in 1993, and received the M.S. degree in mechanical electronic engineering from the Nanjing University of Science and Technology, China, in 2003. Currently, he is a Ph.D. candidate at the School of Automation, Nanjing University of Science and Technology. His current research interests include signal process, neural network, and optimization computation, bearings-only target tracking.
Zhiquan WANG was born in Wuhan, China. He has 30 years of research experience related to nonlinear control, nonlinear dynamic behavior and control in network and data fusion. He is a professor of Nanjing University of Science and Technology and the vice-director of the Automation Association of Jiangsu province. Many projects he was engaged in have won awards including National Science and Technology Progress Awards. In his career, he has published over 100 technical papers and co-authored the book Optimal Control Theory and Systems (Nanjing, China: Southeast University Press, 1994).
Zhengyi WU received the B.S. degree in communication and electronic system from Nanjing Aeronautical and Space-flight University in 1992. He is a senior member of China Computer Federation and Chinese Institute of Electronics. Currently, he is working in Department of Information and Control Engineering, Changshu Institute of Technology as deputy director. His current research interests include multisensor data association, virtual reality and wireless communication technology.
Rights and permissions
About this article
Cite this article
Xu, B., Wang, Z. & Wu, Z. Ant colony optimization for bearings-only maneuvering target tracking in sensors network. J. Control Theory Appl. 5, 301–306 (2007). https://doi.org/10.1007/s11768-005-5190-9
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/s11768-005-5190-9