Name
Abstract | ||
|---|---|---|
This paper proposes a means to achieve tractable particle PHD smoothing through the use of an augmented state space label which tracks the evolution of particles over time. The use of the label reduces the forward-backward particle smoother from quadratic to linear complexity in the number of targets allowing smoothing to be carried out on a large number of targets as well as in the presence of moderate and high levels of clutter. |
Year | Venue | Keywords |
|---|---|---|
2011 | Information Fusion | Monte Carlo methods,particle filtering (numerical methods),probability,smoothing methods,PHD filter,augmented state space label,forward-backward particle smoother,linear complexity,probability hypothesis density,quadratic complexity,sequential Monte Carlo PHD smoothing,tractable particle PHD smoothing,Finite Set Statistics,PHD filters,forward-backward smoothing |
Field | DocType | ISBN |
Monte Carlo method,Mathematical optimization,Clutter,Computer science,Particle filter,Quadratic equation,Smoothing,Linear complexity,State space,Particle | Conference | 978-1-4577-0267-9 |
Citations | PageRank | References |
2 | 0.38 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sharad Nagappa | 1 | 30 | 3.60 |
| Daniel E. Clark | 2 | 360 | 36.76 |