Multitarget Track-Before-Detect via MeMBer Filtering and Track Consistency Test

Abstract:

This paper deals with the problem of time-varying multitarget track-before-detect (TBD) using image observation model. The multitarget state is formulated as random finite set (RFS) and its posterior distribution is approximated by multi-Bernoulli parameters, which are recursively evaluated using sequential Monte Carlo approach. The state estimates are first extracted from the updated Bernoulli components with moderate existence probabilities, allowing for all the true targets and false alarms. The extracted target states are then distilled using track consistency test strategy to remain only the true tracks. Simulation results show the improved performance of the proposed method over the traditional multitarget multi-Bernoulli (MeMBer) filter as well as its capability to provide the identity of individual target.

• Periodical: Applied Mechanics and Materials (Volumes 457-458)
• Pages: 848-855
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.457-458.848
• Online since: October 2013
• Authors: Rong Hui Zhan, Sheng Qi Liu
• Keywords: Multitarget Multi-Bernoulli Filter, Random Finite Set, Track Consistency Test, Track-Before-Detect

References

[1] S. M Tonissen, Y Bar-Shalom, Maximum likelihood track-before-detect with fluctuating target amplitude, IEEE Trans. Aerosp. Electron. Syst., 34(3), 1998, p.796–809.

DOI: 10.1109/7.705887

[2] L. A. Johnston, V. Krishnamuthy, Performance analysis of a dynamic programming track-before-detect algorithm, IEEE Trans. Aerosp. Electron. Syst., 38(1), 2002, p.228–242.

DOI: 10.1109/7.993242

[3] S. J. Davey, M. G. Rutten, B. Cheung, A comparison of detection performance for several track-before-detect algorithms, EURASIP Journal on Advances in Signal Process., vol 2008, 2008, 1–10.

DOI: 10.1155/2008/428036

[4] Y. Boers, J. N. Driessen, Multitarget particle filter track before detect application, IEE Proc-Radar, Sonar, Navig., 151(6), 2004, p.351–357.

DOI: 10.1049/ip-rsn:20040841

[5] M. R. Morelande, C. M. Kreucher, K. Kastella, A Bayesian approach to multiple target detection and tracking, IEEE Trans. Signal Process., 55(5), 2007, p.1589–1604.

DOI: 10.1109/tsp.2006.889470

[6] S. Buzzi, M. Lops, L. Venturino, M. Ferri, Track-before-detect procedures in a multi-target environment, IEEE Trans. Aerosp. Electron. Syst., 44(3), 2008, p.1135–1150.

DOI: 10.1109/taes.2008.4655369

[7] B. K. Habtemariam, R. Tharmarasa, T. Kirubarajan, PHD filter based track-before-detect for MIMO radars, Signal Process., 92, 2012, p.667–678.

DOI: 10.1016/j.sigpro.2011.09.007

[8] S. Arulampalam, S. Maskell, N. Gordan, T. Clapp, A tutorial on particle filter for on-line nonlinear/non-Gaussian Bayesian tracking, IEEE Trans. Signal Process., 50(2), 2002, p.174–188.

DOI: 10.1109/78.978374

[9] R. Mahler, Statistical Multisource-Multitarget Information Fusion. Boston: Artech House, (2007).

[10] B. -N. Vo, B. -T. Vo, N. T. Pham, D. Suter, Joint detection and estimation of multiple objects from image observations, IEEE Trans. Signal Process., 58(10), 2010, p.5129–5241.

DOI: 10.1109/tsp.2010.2050482

[11] R. Hoseinnezhad, B. -N. Vo, B. -T. Vo, D. Suter, Visual tracking of numerous targets via multi-Bernoulli filtering of image data, Pattern Recogn., 45(10), 2012, p.3625–3635.

DOI: 10.1016/j.patcog.2012.04.004

[12] D. Schuhmacher, B. -T. Vo, B. -N. Vo, A consistent metric for performance evaluation of multiobject filters, IEEE Trans. Signal Process., 56(8) , 2008, p.3447–3457.

DOI: 10.1109/tsp.2008.920469