Open Access Open Access  Restricted Access Subscription or Fee Access

An Innovative Approach to More Reliable and Automated Target Characterisation Studies for Underwater Maritime Survelliance

A. Jawahar, Ch. Rajya Lakshmi

Abstract


Target Motion Analysis (TMA) using conventional passive bearing together with frequency measurements is explored. This approach offers one tactical advantage over the classical bearings-only TMA. It makes the ownship maneuver superfluous. In this paper, TMA is carried out using Unscented Kalman Filter (UKF). Inclusion of range, course and speed parameterization is proposed in UKF target state vector to obtain the convergence of the solution fast. Finally the results of various scenarios in Monte-Carlo simulation are presented. This method can be easily adopted for underwater passive target tracking application.


Keywords


Sonar, Estimation, Target Tracking, Ownship, Range, Course, Speed.

Full Text:

PDF

References


Lindgren, A.G., and Gong, K.F (1978), “Position and velocity estimation via bearing Observations”, IEEE Transactions on Aerospace and Electronic Systems, AES-14 (July 1978) 564-577. Aidala, V.J.(1979), “Kalman filter behavior in bearings-only tracking applications.”, IEEE Transactions on Aerospace and Electronic Systems, AES-15(Jan 1979)29-39.

Nardone, S. c., Lindgren, A. G., and Gong, K.F.(1984), “Fundamental properties and performance of conventional bearings-only target motion analysis”, IEEE Transactions on Automatic Control, AC-29 (Sept.1984),775-787.

Aidala, V. J. and Hammel, S.E (1983), “Utilization of modified polar coordinates for bearings-only tracking”, IEEE Transactions on Automatic Control, AC-28 (March.1983),283-294.

T.L. Song and J.L. Speyer (1985), “A stochastic analysis of a modified gain extended Kalman filter with applications to estimation with bearing-only measurements”, IEEE Transactions on Automatic Control, AC-30, No. 10, (Oct. 1985), 940-949.

W. Grossman, “Bearings only tracking: A hybrid coordinate system approach”, J. Guidance, Vol.17, No.3, May-June, 1994, pp 451-459.

Jaffret, C., and Bar-Shalom, Y.(1990),“ Track formation with bearing and frequency measurements”, IEEE Transactions on Aerospace and Electronic Systems, 26,(Nov. 1990),999-1009.

Y.T. Chan and S.W. Rudnicki (1992), “Bearings-only and Doppler-bearing tracking using instrumental variables”, IEEE Transactions on Aerospace and Electronic Systems, 28,(Oct. 1992),1076-1082.

Xiuo-Jiao Tao Cai-Rong Zou and Zhen-Ya He (1996), “Passive target tracking using maximum likelihood estimation”, IEEE Transactions on Aerospace and Electronic Systems, 32,(Oct.1996),1348-1353 .

C. Jauffret and D. Pillon (1996), “Observability in passive target motion analysis”, IEEE Transactions on Aerospace and Electronic Systems, 32,(Oct. 1996),1290-1300

E. A. Wan and R. van der Merwe, “The unscented Kalman filter for nonlinear estimation”, in Proceeding of Symposium 2000 on Adaptive Systems for Signal Processing, Communications and Control, IEEE Lake Louse, Albreta, Canada, October-2000.

K.C. Ho and Y.T. Chan, “An asymptotically unbiased estimator for bearings-only and Doppler-bearing target motion analysis”, IEEE Transactions on Signal Processing, vol.54, No.3, March 2006, 809-821.

Branko Ristic, Sanjeev Arulampalam and Neil Gordon: Beyond the Kalman Filter: Particle Filters for Tracking Applications, Artech House, 2004. M. Morgado, P. Oliveira, C. Silvestre, and J. F. Vasconcelos,

“Embedded vehicle dynamics aiding for USBL/INS underwater

navigation system,” IEEE Transactions on Control Systems Technology, vol. 22, no. 1, pp. 322–330, 2014.

A. Jayasiri, R. G. Gosine, G. K. I. Mann, and P. McGuire, “AUVbased plume tracking: a simulation study,” Journal of Control

Science and Engineering, vol. 2016, Article ID 1764527, 15 pages,

G. E. Packard, A. Kukulya, T. Austin et al., “Continuous

autonomous tracking and imaging of white sharks and basking

sharks using a remus-100 auv,” in Proceedings of the IEEE

OCEANS, pp. 1–5, San Diego, Calif, USA, September 2013.

N. Stilinovic, D. Nad, and N. Miskovic, “Auv for diver assistance

and safety—design and implementation,” in Proceedings of the

OCEANS, pp. 1–4, Geneva, Switzerland, May 2015.

T. Zhang, W. Zeng, L. Wan, and S. Ma, “Underwater target

tracking based on Gaussian particle filter in looking forward

sonar images,” Journal of Computational Information Systems,

vol. 6, no. 14, pp. 4801–4810, 2010.

D. W. Krout, W. Kooiman, G. Okopal, and E. Hanusa, “Object

tracking with imaging sonar,” in Proceedings of the 15th International Conference on Information Fusion (FUSION ’12), pp.

–2405, IEEE, Singapore, September 2012.

K. M. Han and H. T. Choi, “Shape context based object recognition and tracking in structured underwater environment,” in Proceedings of the IEEE International Conference on Geoscience and Remote

Sensing Symposium, pp. 617–620, 2011.

S. Y. Chen, “Kalman filter for robot vision: a survey,” IEEE Transactions on Industrial Electronics, vol. 59, no. 11, pp. 4409–4420, 2012.

D. Eickstedt, M. Benjamin, H. Schmidt et al., “Adaptive tracking of underwater targets with autonomous sensor networks,” Journal of Underwater Acoustics, vol. 56, pp. 465–495, 2006.

H. Shi, W. Wang, N. M. Kwok, and S. Y. Chen, “Game theory for wireless sensor networks: a survey,” Sensors, vol. 12, no. 7, pp. 9055–9097, 2012.

S. Chen, W. Huang, C. Cattani, and G. Altieri, “Traffic dynamics on complex networks: a survey,”Mathematical Problems in Engineering, vol. 2012, Article ID 732698, 23 pages, 2012.

J. Xue, M. Li, W. Zhao, and S. Chen, “Bound maxima as a traffic feature under DDOS flood attacks,”Mathematical Problems in Engineering, vol. 2012, Article ID 419319, 20 pages, 2012.

L. Z. Xu, X. F. Li, and S. X. Yang, “Wireless network and communication signal processing,” Intelligent Automation & Soft Computing, vol. 17, no. 8, article 1019, 2011.

I. F. Akyildiz, D. Pompili, and T. Melodia, “Underwater acoustic sensor networks: research challenges,” Ad Hoc Networks, vol. 3, no. 3, pp. 257–279, 2005.

C. H. Yu, K. H. Lee, J. W. Choi, and Y. B. Seo, “Distributed single target tracking in underwater wireless sensor networks,” in Proceedings of the SICE Annual Conference, pp. 1351–1356, Japan, August 2008.

G. Isbitiren and O. B. Akan, “Three-dimensional underwater target tracking with acoustic sensor networks,” IEEE Transactions on Vehicular Technology, vol. 60, no. 8, pp. 3897–3906, 2011.

E. Kim, S. Lee, C. Kim, and K. Kim, “Bearings-only tracking systems with distributed floating beacons in underwater sensor networks,” in Proceedings of the IEEE/IFIP 8th International Conference

on Embedded and Ubiquitous Computing, (EUC ’10), pp. 311–315, December 2010.

L. Z. Xu, X. F. Ding, X. Wang, G. F. Lv, and F. C. Huang, “Trust region based sequential quasi-Monte Carlo filter,” Acta Electronica Sinica, vol. 39, no. 3 A, pp. 24–30, 2011.

S. Y. Chen and Z. J. Wang, “Acceleration strategies in generalized belief propagation,” IEEE Transactions on Industrial Informatics, vol. 8, no. 1, pp. 41–48, 2012.

X. F. Ding, L. Z. Xu, X. Wang et al., “Robust visual object tracking using covariance features in QuasiMonte Carlo filter,” Intelligent Automation and Soft Computing, vol. 17, no. 5, pp. 571–582, 2011.

X. Wang and Z. Tang, “Modified particle filter-based infrared pedestrian tracking,” Infrared Physics and Technology, vol. 53, no. 4, pp. 280–287, 2010.

S. Y. Chen, H. Tong, Z. Wang, S. Liu, M. Li, and B. Zhang, “Improved generalized belief propagation for vision processing,” Mathematical Problems in Engineering, vol. 2011, Article ID 416963, 12 pages, 2011.

C. Cattani, “Shannon wavelets for the solution of integrodifferential equations,” Mathematical Problems in Engineering, vol. 2010, Article ID 408418, 22 pages, 2010.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.