Results 11 to 20 of about 1,121,998 (275)
Set-membership PHD filter. [PDF]
, 2013 The paper proposes a novel Probability Hypothesis Density (PHD) filter for linear system in which initial state process and measurement noises are only known to be bounded (they can vary on compact sets e.g. polytopes). This means that no probabilistic assumption is imposed on the distributions of initial state and noises besides the knowledge of their
Benavoli A., Papi F.
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A Gaussian mixture PHD filter for extended target tracking [PDF]
2010 13th International Conference on Information Fusion, 2010 In extended target tracking, targets potentially produce more than one measurement per time step. Multiple extended targets are therefore usually hard to track, due to the resulting complex data association. The main contribution of this paper is the implementation of a Probability Hypothesis Density (PHD) filter for tracking of multiple extended ...
Granström, Karl +2 more
core +11 more sources
Convergence Analysis of the Gaussian Mixture PHD Filter [PDF]
IEEE Transactions on Signal Processing, 2007 The Gaussian mixture probability hypothesis density (PHD) filter was proposed recently for jointly estimating the time-varying number of targets and their states from a sequence of sets of observations without the need for measurement-to-track data association.
Daniel Clark, Ba-Ngu Võ
exaly +4 more sources
PHD Filter for Object Tracking in Road Traffic Applications Considering Varying Detectability [PDF]
Sensors, 2021 Tamás Becsi +2 more
exaly +2 more sources
Trajectory PHD and CPHD Filters [PDF]
IEEE Transactions on Signal Processing, 2019 This paper presents the probability hypothesis density filter (PHD) and the cardinality PHD (CPHD) filter for sets of trajectories, which are referred to as the trajectory PHD (TPHD) and trajectory CPHD (TCPHD) filters. Contrary to the PHD/CPHD filters, the TPHD/TCPHD filters are able to produce trajectory estimates from first principles.
Ángel F. García-Fernández +1 more
+9 more sources
A probabilistic hypothesis density filter for traffic flow estimation in the presence of clutter [PDF]
, 2012 Prediction of traffic flow variables such as traffic volume, travel speed or travel time for a short time horizon is of paramount importance in traffic control.
Romain Billot +9 more
core +3 more sources
Fast Implementation of Oversampled Modulated Filter Banks [PDF]
, 2000 This paper presents an efficient implementation of oversampled filter banks derived from a prototype filter by modulation. Via a polyphase analysis, redundancies in the filter operations are removed.
Weiss, Stephan +5 more
core +4 more sources
Probability hypothesis density filtering for real-time traffic state estimation and prediction [PDF]
, 2013 The probability hypothesis density (PHD) methodology is widely used by the research community for the purposes of multiple object tracking. This problem consists in the recursive state estimation of several targets by using the information coming from an
Mihaylova, Lyudmila +9 more
core +3 more sources
Arbitrary clutter extended target probability hypothesis density filter
IET Radar, Sonar & Navigation, 2021 Based on the random finite set (RFS) framework and the probability hypothesis density (PHD) filter, the extended target PHD (ET‐PHD) filter is proposed for multiple extended target tracking.
Xinglin Shen +4 more
doaj +1 more source
A general cardinalized probability hypothesis density filter
EURASIP Journal on Advances in Signal Processing, 2022 Based on random finite set, the probability hypothesis density (PHD) filter and the cardinalized PHD (CPHD) filter have been proposed for multitarget tracking as they are computational tractable.
Xinglin Shen +3 more
doaj +1 more source