The Annals of Applied Probability

Analysis of error propagation in particle filters with approximation

Boris N. Oreshkin and Mark J. Coates

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This paper examines the impact of approximation steps that become necessary when particle filters are implemented on resource-constrained platforms. We consider particle filters that perform intermittent approximation, either by subsampling the particles or by generating a parametric approximation. For such algorithms, we derive time-uniform bounds on the weak-sense Lp error and present associated exponential inequalities. We motivate the theoretical analysis by considering the leader node particle filter and present numerical experiments exploring its performance and the relationship to the error bounds.

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Ann. Appl. Probab., Volume 21, Number 6 (2011), 2343-2378.

First available in Project Euclid: 23 November 2011

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Primary: 62L12: Sequential estimation 65C35: Stochastic particle methods [See also 82C80] 65L20: Stability and convergence of numerical methods

Collaborative tracking particle filtering error analysis


Oreshkin, Boris N.; Coates, Mark J. Analysis of error propagation in particle filters with approximation. Ann. Appl. Probab. 21 (2011), no. 6, 2343--2378. doi:10.1214/11-AAP760.

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