[1] Vo B N, Vo B T, Hoang H G. An efficient implementation of the generalized labeled multi-Bernoulli filter. IEEE Transactions on Signal Processing, 2017, 65(8): 1975-1987 doi: 10.1109/TSP.2016.2641392
[2] Gostar A K, Hoseinnezhad R, Bab-Hadiashar A, et al. Sensor-management for multitarget filters via minimization of posterior dispersion. IEEE Transactions on Aerospace and Electronic Systems, 2017, 53(6): 2877-2884 doi: 10.1109/TAES.2017.2718280
[3] Xia Y X, Granström K, Svensson L, Fatemi M. Extended target Poisson Multi-Bernoulli filter. arXiv: 1801.01353, 2018.
[4] Cao W, Lan J, Li X R. Extended object tracking and classification using radar and ESM sensor data. IEEE Signal Processing Letters, 2018, 25(1): 90-94 doi: 10.1109/LSP.2017.2757920
[5] Granström K, Baum M, Reuter S. Extended object tracking: introduction, overview, and applications. Journal of Advances in Information Fusion, 2017, 12(2): 139-174 http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ026837439/
[6] Sun L F, Lan J, Li X R. Joint tracking and classification of extended object based on support functions. IET Radar, Sonar & Navigation, 2018, 12(7): 685-693 http://cn.bing.com/academic/profile?id=f0ee724952593df098352f581578ff5d&encoded=0&v=paper_preview&mkt=zh-cn
[7] Aftab W, De Freitas A, Arvaneh M, Mihaylova L. A Gaussian process approach for extended object tracking with random shapes and for dealing with intractable likelihoods. In: Proceedings of the 22nd International Conference on Digital Signal Processing (DSP). London, UK: IEEE, 2017. 1-5
[8] Beard M, Reuter S, Granström K, Vo B T, Vo B N, Scheel A. Multiple extended target tracking with labeled random finite sets. IEEE Transactions on Signal Processing, 2016, 64(7): 1638-1653 doi: 10.1109/TSP.2015.2505683
[9] Mahler R P S. Advances in Statistical Multisource-Multitarget Information Fusion. Boston, USA: Artech House, 2014.
[10] Mahler R P S. Statistical Multisource-Multitarget Information Fusion. Boston, USA: Artech House, Inc., 2007.
[11] Mahler R P S. Multitarget Bayes filtering via first-order multitarget moments. IEEE Transactions on Aerospace and Electronic Systems, 2003, 39(4): 1152-1178 doi: 10.1109/TAES.2003.1261119
[12] Mahler R. PHD filters of higher order in target number. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(4): 1523-1543 doi: 10.1109/TAES.2007.4441756
[13] 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 doi: 10.1109/TSP.2008.2007924
[14] Vo B T, Vo B N, Phung D. Labeled random finite sets and the Bayes multi-target tracking filter. IEEE Transactions on Signal Processing, 2014, 62(24): 6554-6567 doi: 10.1109/TSP.2014.2364014
[15] Vo B N, Vo B T. An implementation of the multi-sensor generalized labeled multi-Bernoulli filter via Gibbs sampling. In: Proceedings of the 20th International Conference on Information Fusion. Xi'an, China: IEEE, 2017: 1-8
[16] Vo B N, Vo B T, Beard M. Multi-sensor multi-object tracking with the generalized labeled multi-Bernoulli filter. IEEE Transactions on Signal Processing, 2019, 67(23): 5952-5967 doi: 10.1109/TSP.2019.2946023
[17] Hoseinnezhad R, Vo B N, Vo B T, Suter D. Bayesian integration of audio and visual information for multi-target tracking using a CB-MeMBer filter. In: Proceedings of the 2011 International Conference on Acoustics, Speech and Signal Processing (ICASSP). Prague, Czech Republic: IEEE, 2011. 2300-2303
[18] Chong N, Nordholm S, Vo B T, Murray I. Tracking and separation of multiple moving speech sources via cardinality balanced multi-target multi Bernoulli (CBMeMBer) filter and time frequency masking. In: Proceedings of the 2016 International Conference on Control, Automation and Information Sciences (ICCAIS). Ansan, South Korea: IEEE, 2016. 88-93
[19] Hoang H G, Vo B T. Sensor management for multi-target tracking via multi-Bernoulli filtering. Automatica, 2014, 50(4): 1135-1142 doi: 10.1016/j.automatica.2014.02.007
[20] 陈辉, 韩崇昭.机动多目标跟踪中的传感器控制策略的研究.自动化学报, 2016, 42(4): 512-523 doi: 10.16383/j.aas.2016.c150529

Chen Hui, Han Chong-Zhao. Sensor control strategy for maneuvering multi-target tracking. Acta Automatica Sinica, 2016, 42(4): 512-523 doi: 10.16383/j.aas.2016.c150529
[21] Gilholm K, Salmond D. Spatial distribution model for tracking extended objects. IEE Proceedings-Radar, Sonar and Navigation, 2005, 152(5): 364-371 doi: 10.1049/ip-rsn:20045114
[22] Gilholm K, Godsill S, Maskell S, Salmond D. Poisson models for extended target and group tracking. In: Proceedings of SPIE 5913, Signal and Data Processing of Small Targets 2005. San Diego, USA: SPIE, 2005. 230-241
[23] Lan J, Li X R. Tracking of extended object or target group using random matrix—Part Ⅱ: irregular object. In: Proceedings of the 15th International Conference on Information Fusion. Singapore: IEEE, 2012. 2185-2192
[24] Lan J, Li X R. Tracking of maneuvering non-ellipsoidal extended object or target group using random matrix. IEEE Transactions on Signal Processing, 2014, 62(9): 2450-2463 doi: 10.1109/TSP.2014.2309561
[25] Feldmann M, Franken D. Tracking of extended objects and group targets using random matrices—a new approach. In: Proceedings of the 11th International Conference on Information Fusion. Cologne, Germany: IEEE, 2008. 1-8
[26] Feldmann M, Fränken D, Koch W. Tracking of extended objects and group targets using random matrices. IEEE Transactions on Signal Processing, 2011, 59(4): 1409-1420 doi: 10.1109/TSP.2010.2101064
[27] Orguner U. A variational measurement update for extended target tracking with random matrices. IEEE Transactions on Signal Processing, 2012, 60(7): 3827-3834 doi: 10.1109/TSP.2012.2192927
[28] Baum M, Hanebeck U D. Extended object tracking with random hypersurface models. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(1): 149-159 doi: 10.1109/TAES.2013.120107
[29] Baum M, Hanebeck U D. Shape tracking of extended objects and group targets with star-convex RHMs. In: Proceedings of the 14th International Conference on Information Fusion. Chicago, USA: IEEE, 2011. 338-345
[30] Zea A, Faion F, Baum M, Hanebeck U D. Level-set random hypersurface models for tracking nonconvex extended objects. IEEE Transactions on Aerospace and Electronic Systems, 2016, 52(6): 2990-3007 doi: 10.1109/TAES.2016.130704
[31] Yao G, Dani A. Image moment-based random hypersurface model for extended object tracking. In: Proceedings of the 20th International Conference on Information Fusion. Xi'an, China: IEEE, 2017. 1-7
[32] Han Y L, Zhu H Y, Han C. A Gaussian-mixture PHD filter based on random hypersurface model for multiple extended targets. In: Proceedings of the 16th International Conference on Information Fusion. Istanbul, Turkey: IEEE, 2013. 1752-1759
[33] Ünsalan C, Erçil A. Conversions between parametric and implicit forms using polar/spherical coordinate representations. Computer Vision and Image Understanding, 2001, 81(1): 1-25 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=e8862acbb2ed9a24a7854026578db0ff
[34] Zhang G H, Lian F, Han C Z. CBMeMBer filters for nonstandard targets, Ⅰ: extended targets. In: Proceedings of the 17th International Conference on Information Fusion. Salamanca, Spain: IEEE, 2014. 1-6
[35] Arasaratnam I, Haykin S, Hurd T R. Cubature Kalman filtering for continuous-discrete systems: theory and simulations. IEEE Transactions on Signal Processing, 2010, 58(10): 4977-4993 doi: 10.1109/TSP.2010.2056923
[36] Schuhmacher D, Vo B T, Vo B N. A consistent metric for performance evaluation of multi-object filters. IEEE Transactions on Signal Processing, 2008, 56(8): 3447-3457 doi: 10.1109/TSP.2008.920469