@Article{PardalKugaMora:2015:PaFiSa,
author = "Pardal, Paula Cristiane Pinto Mesquita and Kuga, H{\'e}lio Koiti
and Moraes, Rodolpho Vilhena de",
affiliation = "{Universidade de S{\~a}o Paulo (USP)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Universidade Federal de S{\~a}o
Paulo (UNIFESP)}",
title = "The particle filter sample impoverishment problem in the orbit
determination application",
journal = "Mathematical Problems in Engineering",
year = "2015",
volume = "2015",
pages = "168045",
abstract = "The paper aims at discussing techniques for administering one
implementation issue that often arises in the application of
particle filters: sample impoverishment. Dealing with such problem
can significantly improve the performance of particle filters and
can make the difference between success and failure. Sample
impoverishment occurs because of the reduction in the number of
truly distinct sample values. A simple solution can be to increase
the number of particles, which can quickly lead to unreasonable
computational demands, which only delays the inevitable sample
impoverishment. There are more intelligent ways of dealing with
this problem, such as roughening and prior editing, procedures to
be discussed herein. The nonlinear particle filter is based on the
bootstrap filter for implementing recursive Bayesian filters. The
application consists of determining the orbit of an artificial
satellite using real data from the GPS receivers. The standard
differential equations describing the orbital motion and the GPS
measurements equations are adapted for the nonlinear particle
filter, so that the bootstrap algorithm is also used for
estimating the orbital state. The evaluation will be done through
convergence speed and computational implementation complexity,
comparing the bootstrap algorithm results obtained for each
technique that deals with sample impoverishment.",
doi = "10.1155/2015/168045",
url = "http://dx.doi.org/10.1155/2015/168045",
issn = "1024-123X",
language = "en",
urlaccessdate = "04 dez. 2020"
}