Multiple model algorithm based on particle filters for ground target tracking
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[1] Hedvig Sidenbladh,et al. Multi-target particle filtering for the probability hypothesis density , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.
[2] Krishna R. Pattipati,et al. Ground target tracking with variable structure IMM estimator , 2000, IEEE Trans. Aerosp. Electron. Syst..
[3] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[4] L. Sjoberg,et al. Ground target tracking using acoustic sensors , 2007, 2007 Information, Decision and Control.
[5] Y. Boers,et al. Efficient particle filter for jump Markov nonlinear systems , 2005 .
[6] Hans Driessen,et al. IMM algorithm based on a hybrid bootstrap filter , 2000, SPIE Defense + Commercial Sensing.
[7] Y. Bar-Shalom,et al. The interacting multiple model algorithm for systems with Markovian switching coefficients , 1988 .
[8] Niclas Bergman,et al. Recursive Bayesian Estimation : Navigation and Tracking Applications , 1999 .
[9] Rickard Karlsson,et al. Particle filtering for positioning and tracking applications , 2005 .
[10] Y. Boers,et al. A Particle Filter Multi Target Track Before Detect Application : Some Special Aspects , 2004 .
[11] Nando de Freitas,et al. Sequential Monte Carlo in Practice , 2001 .
[12] David J. Salmond. Mixture reduction algorithms for target tracking in clutter , 1990 .
[13] Nando de Freitas,et al. Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.
[14] Branko Ristic,et al. Beyond the Kalman Filter: Particle Filters for Tracking Applications , 2004 .