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Speedup and tracking accuracy evaluation of parallel particle filter algorithms implemented on a multicore architecture

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3 Author(s)
Olov Rosén ; Institution of Information Technology, Department of System and Control, Uppsala University, SE-751 05, Sweden ; Alexander Medvedev ; Mats Ekman

Four different parallel particle filters such as globally distributed particle filter (GDPF), resampling with proportional allocation filter (RPA), resampling with non-proportional allocation filter (RNA) and the Gaussian particle filter (GPF), are studied in terms of speedup and tracking accuracy in a bearings-only tracking problem. The filters are implemented on a shared memory multicore computer, where the speedup is measured using up to eight cores. The tracking accuracy is studied in a simulated BOT application where the GPF exhibits best tracking accuracy, and RNA, RPA and GDPF give tracking accuracy comparable to the sequential particle filter. Both GPF and RNA appear to be capable of achieving linear speedup in the number of cores used, while RPA shows somewhat less encouraging speedup and GDPF is found to have a speedup limited to about 3 times.

Published in:

2010 IEEE International Conference on Control Applications

Date of Conference:

8-10 Sept. 2010