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 :
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