DocumentCode
3642134
Title
Efficient distributed resampling for particle filters
Author
Balakumar Balasingam;Miodrag Bolić;Petar M. Djurić;Joaquín Míguez
Author_Institution
School of Information Technology and Engineering, University of Ottawa (Canada)
fYear
2011
fDate
5/1/2011 12:00:00 AM
Firstpage
3772
Lastpage
3775
Abstract
In particle filtering, resampling is the only step that cannot be fully parallelized. Recently, we have proposed algorithms for distributed resampling implemented on architectures with concurrent processing elements (PEs). The objective of distributed resampling is to reduce the communication among the PEs while not compromising the performance of the particle filter. An additional objective for implementation is to reduce the communication among the PEs. In this paper, we report an improved version of the distributed resampling algorithm that optimally selects the particles for communication between the PEs of the distributed scheme. Computer simulations are provided that demonstrate the improved performance of the proposed algorithm.
Keywords
"Copper","Signal processing algorithms","Probability density function","Signal processing","Markov processes","Approximation algorithms","Covariance matrix"
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
ISSN
1520-6149
Print_ISBN
978-1-4577-0538-0
Electronic_ISBN
2379-190X
Type
conf
DOI
10.1109/ICASSP.2011.5947172
Filename
5947172
Link To Document