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[1]
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Pulford G E. Taxonomy of multiple target tracking methods. IEE Proceedings of Radar, Sonar and Navigation}, 2005, 152(5): 291-304[2] Blackman S, Popoli R. Design and Analysis of Modern Tracking Systems. Norwood: Artech House, 1999[3] Daley D, Vere-jones D. An Introduction to the Theory of Point Processes. Second Edition. New York: Springer-Verlag, 2002[4] Mahler R P S. Multitarget Bayes filtering via first-order multitarget moments. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(4): 1152-1178[5] Mahler R P S. Statistical Multisource-Multitarget Information Fusion. Norwood: Artech House, 2007[6] Erdinc O, Willett P, Bar-shalom Y. The bin-occupancy filter and its connection to the PHD filters. IEEE Transactions on Signal Processing, 2009, 57(11): 4232-4246[7] Vo B N, Singh S, Doucet A. Sequential Monte Carlo methods for multitarget filtering with random finite sets. IEEE Transactions on Aerospace and Electronic Systems, 2005, 41(4): 1224-1245[8] Whiteley N, Singh S, Godsill S. Auxiliary particle implementation of probability hypothesis density filter. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(3): 1437-1454[9] Liu W F, Han C Z, Lian F, Zhu H Y. Multitarget state extraction for the PHD filter using MCMC approach. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(2): 864-883[10] Vo B N, Ma W K. The Gaussian mixture probability hypothesis density filter. IEEE Transactions on Signal Processing, 2006, 54(11): 4091-4104[11] Pasha S A, Vo B N, Tuan H D, Ma W K. A Gaussian mixture PHD filter for jump Markov system models. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(3): 919-936[12] Clark D E, Bell J. Convergence results for the particle PHD filter. IEEE Transactions on Signal Processing, 2006, 54(7): 2652-2661[13] Clark D E, Vo B N. Convergence analysis of the Gaussian mixture PHD filter. IEEE Transactions on Signal Processing, 2007, 55(4): 1204-1212[14] Mahler R P S. PHD filters of higher order in target number. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(4): 1523-1543[15] Vo B T, Vo B N, Cantoni A. The cardinality balanced multi-target multi-Bernoulli filter and its implementations. IEEE Transactions on Signal Processing, 2009, 57(2): 409-423[16] Franken D, Schmidt M, Ulmke M. "Spooky action at a distance" in the cardinalized probability hypothesis density filter. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(4): 1657-1664[17] Vo B T, Vo B N, Cantoni A. Analytic implementations of the cardinalized probability hypothesis density filter. IEEE Transactions on Signal Processing, 2007, 55(7): 3553-3567[18] Zhang H J, Jing Z L, Hu S Q. Gaussian mixture CPHD filter with gating technique. Signal Processing, 2009, 89(8): 1521-1530[19] Punithakumar K, Kirubarajan T, Sinha A. Multiple-model probability hypothesis density filter for tracking maneuvering targets. IEEE Transactions on Aerospace and Electronic Systems, 2008, 44(1): 87-98[20] Lian Feng, Han Chong-Zhao, Liu Wei-Feng, Yuan Xiang-Hui. Multiple-model probability hypothesis density smoother. Acta Automatica Sinica, 2010, 36(7): 939-950 (连峰, 韩崇昭, 刘伟峰, 元向辉. 多模型概率假设密度平滑器. 自动化学报, 2010, 36(7): 939-950)[21] Clark D E, Bell J. Multi-target state estimation and track continuity for the particle PHD filter. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(4): 1441-1453[22] Panta K, Clark D, Vo B N. Data association and track management for the Gaussian mixture probability hypothesis density filter. IEEE Transactions on Aerospace and Electronic Systems, 2009, 45(3): 1003-1016[23] Vo B T, Vo B N, Cantoni A. Bayesian filtering with random finite set observations. IEEE Transactions on Signal Processing, 2008, 56(4): 1313-1326[24] Rezaeian M, Vo B N. Error bounds for joint detection and estimation of a single object with random finite set observation. IEEE Transactions on Signal Processing, 2010, 58(3): 1493-1506[25] Wang Y D, Wu J K, Kassim A A, Huang W M. Data-driven probability hypothesis density filter for visual tracking. IEEE Transactions on Circuits and Systems for Video Technology, 2008, 18(8): 1085-1095[26] Maggio E, Taj M, Cavallaro A. Efficient multitarget visual tracking using random finite sets. IEEE Transactions on Circuits and Systems for Video Technology, 2008, 18(8): 1016-1027[27] Maggio E, Cavallaro A. Learning scene context for multiple object tracking. IEEE Transactions on Image Processing, 2009, 18(8): 1873-1884[28] Clark D, Ruiz I T, Petilot Y, Bell J. Particle PHD filter multiple target tracking in sonar images. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(1): 409-416[29] Clark D, Ristic B, Vo B N, Vo B T. Bayesian multi-object filtering with amplitude feature likelihood for unknown object SNR. IEEE Transactions on Signal Processing, 2010, 58(1): 26-37[30] Zhang H J, Jing Z L, Hu S Q. Localization of multiple emitters based on the sequential PHD filter. Signal Processing, 2010, 90(1): 34-43[31] Mclachlan G, Peel D. Finite Mixture Models}. New York: John Wiley and Sons, 2000 \vskip 5mm[32] Davy M, Tourneret J Y. Generative supervised classification using Dirichlet process priors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(10): 1781-1794[33] Figueiredo M A F, Jain A K. Unsupervised learning of finite mixture models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(3): 381-396[34] Hoffman J R, Mahler R P S. Multitarget miss distance via optimal assignment. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2004, 34(3): 327-336 }
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