DocumentCode
549156
Title
Fast sequential Monte Carlo PHD smoothing
Author
Nagappa, Sharad ; Clark, Daniel E.
Author_Institution
Sch. of EPS, Heriot Watt Univ., Edinburgh, UK
fYear
2011
fDate
5-8 July 2011
Firstpage
1
Lastpage
7
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.
Keywords
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; Clutter; Complexity theory; Equations; Labeling; Mathematical model; Smoothing methods; Target tracking; Finite Set Statistics; PHD filters; forward-backward smoothing;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on
Conference_Location
Chicago, IL
Print_ISBN
978-1-4577-0267-9
Type
conf
Filename
5977594
Link To Document