Survey of maneuvering target tracking. Part V. Multiple-model methods

By X. Rong Li, Vesselin P. Jilkov. IEEE Transactions on Aerospace and Electronic Systems, 2005

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Bayesian Nonparametric Inference of Switching Dynamic Linear Models (2010, background): “INTRODUCTION Linear dynamical systems (LDSs) are useful in describing dy namical phenomena as diverse as human motion [3], [4], financial time-series [5]–[7], maneuverin g targets [8], [9], and the dance of honey bees [10].”
Survey of maneuvering target tracking. Part I. Dynamic models (2003, background): “In general, one can say without exaggeration that a good model is worth a thousand pieces of data.”
Human motion trajectory prediction: a survey (2019, methodology): “Following (Li and Jilkov 2005), MM methods generally consist of four elements: a ﬁxed or on-line adaptive model set, a strategy to deal with the discrete-valued uncertainties, for example, model sequences under a Markov or semi-Markov assumption, a recursive estimation scheme to deal with the…”
Objective comparison of particle tracking methods (2014, methodology): “METHOD 4: PARAMETERS The user parameters of this method (and typical values) are:  Number of iterations of convolution with the Gaussian kernel (10-500).”
Survey of Maneuvering Target Tracking. Part II: Motion Models of Ballistic and Space Targets (2010, background): “The reader is referred to the recent surveys [66, 58, 68, 59].”