TY - JOUR
T1 - Resampling Methods for Particle Filtering
T2 - Classification, implementation, and strategies
AU - Li, Tiancheng
AU - Bolić, Miodrag
AU - Djurić, Petar M.
N1 - Publisher Copyright:
© 1991-2012 IEEE.
PY - 2015/5/1
Y1 - 2015/5/1
N2 - Two decades ago, with the publication of [1], we witnessed the rebirth of particle filtering (PF) as a methodology for sequential signal processing. Since then, PF has become very popular because of its ability to process observations represented by nonlinear state-space models where the noises of the model can be non-Gaussian. This methodology has been adopted in various fields, including finance, geophysical systems, wireless communications, control, navigation and tracking, and robotics [2]. The popularity of PF has also spurred the publication of several review articles [2]-[6].
AB - Two decades ago, with the publication of [1], we witnessed the rebirth of particle filtering (PF) as a methodology for sequential signal processing. Since then, PF has become very popular because of its ability to process observations represented by nonlinear state-space models where the noises of the model can be non-Gaussian. This methodology has been adopted in various fields, including finance, geophysical systems, wireless communications, control, navigation and tracking, and robotics [2]. The popularity of PF has also spurred the publication of several review articles [2]-[6].
UR - http://www.scopus.com/inward/record.url?scp=85032752371&partnerID=8YFLogxK
U2 - 10.1109/MSP.2014.2330626
DO - 10.1109/MSP.2014.2330626
M3 - 文章
AN - SCOPUS:85032752371
SN - 1053-5888
VL - 32
SP - 70
EP - 86
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 3
M1 - 7079001
ER -