Comparison and error analysis of integral-free Kalman tracking filter algorithms
Hongyan Wang, Yu Daobin, Jiawei Jiang · 2014
The integral-free Kalman filters which are widely used in target tracking are studied. The algorithms of Unscented Kalman filter (UKF), Cubature Kalman filter (CKF) and Square-root cubature Kalman filter (SCKF) are compared in details. A modified algorithm (MSCKF) is proposed to optimize the performance. When considering different original ranges and radial speeds, simulation of linear motion targets in Gauss noise is made and their tracking errors are analyzed. The result shows that different tracking filter algorithm has respective features in short time and long range signal processing. The MSCKF has better tracking performance in short time tracking application. It offers the guideline for application.