Adaptation of Scaling Parameter for Unscented Kalman Filter Target Tracking Algorithm
WANG Jianhong
XU Ying
XIONG Zhaohua
Abstract：The state estimation problem of the nonlinear stochastic systems is studied by means of the unscented Kal‐man filter algorithm from target tracking process .In the unscented Kalman filter algorithm ,the state estimation is influenced by two design parameters — the scaling parameter and a covariance matrix .Because the choice of scaling parameter may lead to the increased quality of the state estimation .So here the four different criterion functions are constructed ,and the scaling parameter is chosen adaptively by minimizing one criterion function .The property of each four criterion functions is shown from their own different observed information and computation complexity .Finally ,the efficiency and possibility of the adap‐tation of scaling parameter for unscented Kalman filter target tracking algorithm is confirmed by the simulation example re‐sults .
Keywords：target trackingunscented Kalman filterscaling parameteradaptation
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 39-43 )