access icon free Particle filter based on one-step smoothing with adaptive iteration

© The Institution of Engineering and Technology
Received 05/04/2016, Accepted 31/01/2017, Revised 22/12/2016, Published 11/02/2017

A new one-step particle smoother is explicitly given in the form of proper weighted samples. It is employed iteratively to improve the importance sampling in particle filtering through incorporating the current measurement information into the a priori distribution. An adaptive iteration strategy is proposed to accelerate the running, which introduces a parameter into the weight increment to adjust the iteration process. Then, new particle filtering method can be constructed through combining the one-step smoothing and the adaptive iteration strategy.

Inspec keywords: iterative methods; smoothing methods; particle filtering (numerical methods); signal sampling

Other keywords: particle filtering method; proper weighted samples; importance sampling; one-step particle smoother; adaptive iteration strategy; a priori distribution; current measurement information; iteration process

Subjects: Filtering methods in signal processing; Signal processing theory; Interpolation and function approximation (numerical analysis); Interpolation and function approximation (numerical analysis)

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