Joint tracking and classification based on recursive joint decision and estimation using multi-sensor data
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[1] Lang Hong,et al. Wavelets feature aided tracking (WFAT) using GMTI/HRR data , 2003, Signal Process..
[2] Zhansheng Duan,et al. Comprehensive evaluation of decision performance , 2008, 2008 11th International Conference on Information Fusion.
[3] Wei Mei,et al. Simultaneous tracking and classification: a modularized scheme , 2007, IEEE Transactions on Aerospace and Electronic Systems.
[4] Yu Liu,et al. Recursive joint decision and estimation based on generalized Bayes risk , 2011, 14th International Conference on Information Fusion.
[5] Donka Angelova,et al. Sequential Monte Carlo algorithms for joint target tracking and classification using kinematic radar information , 2004 .
[6] X. Rong Li,et al. Optimal bayes joint decision and estimation , 2007, 2007 10th International Conference on Information Fusion.
[7] A. Farina,et al. Joint tracking and identification algorithms for multisensor data , 2002 .
[8] Y. Bar-Shalom,et al. Tracking with classification-aided multiframe data association , 2003, IEEE Transactions on Aerospace and Electronic Systems.
[9] LI X.RONG,et al. Evaluation of estimation algorithms part I: incomprehensive measures of performance , 2006, IEEE Transactions on Aerospace and Electronic Systems.
[10] X. Rong Li,et al. Joint tracking and classification of extended object using random matrix , 2013, Proceedings of the 16th International Conference on Information Fusion.
[11] Kuo-Chu Chang,et al. Target identification with Bayesian networks in a multiple hypothesis tracking system , 1997 .
[12] M. L. Krieg,et al. Joint multi-sensor kinematic and attribute tracking using Bayesian belief networks , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.
[13] H. Raiffa,et al. Applied Statistical Decision Theory. , 1961 .
[14] J.A. O'Sullivan,et al. Automatic target recognition using kinematic priors , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.
[15] Yakov Bar-Shalom,et al. Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .
[16] T. Kurien. Framework for integrated tracking and identification of multiple targets , 1991, IEEE/AIAA 10th Digital Avionics Systems Conference.
[17] Subhash Challa,et al. Joint target tracking and classification using radar and ESM sensors , 2001 .
[18] Hans Driessen,et al. Integrated tracking and classification: an application of hybrid state estimation , 2001, SPIE Optics + Photonics.
[19] X. R. Li,et al. Measures of performance for evaluation of estimators and filters , 2001 .
[20] Branko Ristic,et al. On target classification using kinematic data , 2004, Inf. Fusion.
[21] Ming Yang,et al. Joint tracking and classification based on bayes joint decision and estimation , 2007, 2007 10th International Conference on Information Fusion.
[22] Raman K. Mehra,et al. Joint tracking, pose estimation, and identification using HRRR data , 2000, SPIE Defense + Commercial Sensing.
[23] X. Rong Li,et al. Extended object tracking and classification based on recursive joint decision and estimation , 2013, Proceedings of the 16th International Conference on Information Fusion.
[24] Thia Kirubarajan,et al. Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software , 2001 .
[25] D. Marshall,et al. Joint tracking and classification of nonlinear trajectories of multiple objects using the transferable belief model and multi-sensor fusion framework , 2005, 2005 7th International Conference on Information Fusion.