Open AccessModified Unscented Kalman Filter for a Multirate INS/GPS Integrated Navigation System
Author(s) -
Enkhtur Munkhzul,
Cho Seong Yun,
Kim KyongHo
Publication year - 2013
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.13.0212.0540
Subject(s) - kalman filter , inertial navigation system , global positioning system , gps/ins , navigation system , control theory (sociology) , unscented transform , computer science , extended kalman filter , filter (signal processing) , engineering , fast kalman filter , assisted gps , real time computing , artificial intelligence , inertial frame of reference , computer vision , telecommunications , control (management) , physics , quantum mechanics
Instead of the extended Kalman filter, the unscented Kalman filter (UKF) has been used in nonlinear systems without initial accurate state estimates over the last decade because the UKF is robust against large initial estimation errors. However, in a multirate integrated system, such as an inertial navigation system (INS)/Global Positioning System (GPS) integrated navigation system, it is difficult to implement a UKF‐based navigation algorithm in a low‐grade or mid‐grade microcontroller, owing to a large computational burden. To overcome this problem, this letter proposes a modified UKF that has a reduced computational burden based on the basic idea that the change of probability distribution for the state variables between measurement updates is small in a multirate INS/GPS integrated navigation filter. The performance of the modified UKF is verified through numerical simulations.