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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Introduction to the Box Particle Filtering
AU - Gning, Amadou
AU - Ristic, B
AU - Mihaylova, Lyudmila
AU - Abdallah, F.
PY - 2013/6/12
Y1 - 2013/6/12
N2 - This paper presents a novel method for solving nonlinear filtering problems. This approach is particularly appealing in practical situations involving imprecise stochastic measurements, thus resulting in very broad posterior densities. It relies on the concept of a box particle, which occupies a small and controllable rectangular region having a non-zero volume in the state space. Key advantages of the box particle filter (Box-PF) against the standard particle filter (PF) are in its reduced computational complexity and its suitability for distributed filtering. Indeed, in some applications where the sequential importance resampling (SIR) PF may require thousands of particles to achieve an accurate and reliable performance, the Box-PF can reach the same level of accuracy with just a few dozens of box particles.
AB - This paper presents a novel method for solving nonlinear filtering problems. This approach is particularly appealing in practical situations involving imprecise stochastic measurements, thus resulting in very broad posterior densities. It relies on the concept of a box particle, which occupies a small and controllable rectangular region having a non-zero volume in the state space. Key advantages of the box particle filter (Box-PF) against the standard particle filter (PF) are in its reduced computational complexity and its suitability for distributed filtering. Indeed, in some applications where the sequential importance resampling (SIR) PF may require thousands of particles to achieve an accurate and reliable performance, the Box-PF can reach the same level of accuracy with just a few dozens of box particles.
KW - sequential Monte Carlo methods
KW - Particle methods
KW - uncertainty
KW - Uniform distribution
KW - Box particle filter
KW - tracking
U2 - 10.1109/MSP.2013.2254601
DO - 10.1109/MSP.2013.2254601
M3 - Journal article
VL - 30
SP - 166
EP - 171
JO - IEEE Signal Processing Magazine
JF - IEEE Signal Processing Magazine
IS - 4
ER -