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Data centric SIR particle filter design using buffer-level pipelining

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we introduce use of sample importance resampling (SIR) particle filter for bearings-only tracking problem using buffer-level pipelining. The SIR particle filter is heavily data centric in that it transfer significant amount of data between processing blocks. We propose to design the overall filter using buffer-level pipelining where design flow can be significantly simplified. In the buffer-level pipelining, overall execution synchronization is done through controlling patterns of data producing and consuming by each processing block. We verify temporal operation of the filter using Verilog and SystemC.

Original languageEnglish
Title of host publication2004 7th International Conference on Signal Processing Proceedings, ICSP
Pages2467-2470
Number of pages4
StatePublished - 2004
Event2004 7th International Conference on Signal Processing Proceedings, ICSP - Beijing, China
Duration: Aug 31 2004Sep 4 2004

Publication series

Name2004 7th International Conference on Signal Processing Proceedings, ICSP

Conference

Conference2004 7th International Conference on Signal Processing Proceedings, ICSP
Country/TerritoryChina
CityBeijing
Period08/31/0409/4/04

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