Comparison of Particle Filter and Unscented Particle Filter Algorithms
ZHENG Chenyao
DONG Zhenjie
ZHANG Weiquan
Abstract：To resolve the underwater acoustic position precision and tracking ,this paper establishes a dynamic nonlinear non‐Gaussian model .The particle filter directly employs the state transition prior distribution function which does not include the latest measuring information as an importance density function to approximate the posterior density function .The un‐scented paticle filter brings in resampling technique ,develops the importance density function by unscented transformation that is more close to the posterior density .Simulation results demonstrate that paticle filter and unscented paticle filter all can increase the precision of target position and tracking ,but there is higher estimation precision with the latter .The algorithm of unscented paticle filter is more suitable for engineering pactice .
Keywords：unscented particle filternonlinear non-gaussianimportance density functionresamplingposition preci-sion and tracking
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 47-49,61 )