Efficient distributed resampling for particle filters
Document Type
Conference Proceeding
Publication Date
8-18-2011
Publication Title
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
First Page
3772
Keywords
distributed resampling, particle filters, Sequential Monte-Carlo methods
Last Page
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. © 2011 IEEE.
DOI
10.1109/ICASSP.2011.5947172
ISSN
15206149
ISBN
9781457705397
Recommended Citation
Balasingam, Balakumar; Bolić, Miodrag; Djurić, Petar M.; and Míguez, Joaquín. (2011). Efficient distributed resampling for particle filters. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 3772-3775.
https://scholar.uwindsor.ca/computersciencepub/164