Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing
作者机构：Department of CommunicationsNavigation and Control EngineeringTaiwan Ocean UniversityKeelung202301Taiwan
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2021年第68卷第7期
页 面：857-876页
核心收录：
学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学]
基 金：supported by the Ministry of Science and Technology Taiwan(Grant Number MOST 108-2221-E-019-013)
主 题：GPS satellite navigation extended Kalman filter entropy correntropy multipath non-Gaussian
摘 要：This paper investigates the kernel entropy based extended Kalman filter(EKF)as the navigation processor for the Global Navigation Satellite Systems(GNSS),such as the Global Positioning System(GPS).The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed(or impulsive)interference errors,such as the *** kernel minimum error entropy(MEE)and maximum correntropy criterion(MCC)based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the *** standard EKF method is derived based on minimization of mean square error(MSE)and is optimal only under Gaussian assumption in case the system models are precisely *** GPS navigation algorithm based on kernel entropy related principles,including the MEE criterion and the MCC will be performed,which is utilized not only for the time-varying adaptation but the outlier type of interference *** kernel entropy based design is a new approach using information from higher-order signal *** information theoretic learning(ITL),the entropy principle based measure uses information from higher-order signal statistics and captures more statistical information as compared to *** improve the performance under non-Gaussian environments,the proposed filter which adopts the MEE/MCC as the optimization criterion instead of using the minimum mean square error(MMSE)is utilized for mitigation of the heavy-tailed type of multipath *** assessment will be carried out to show the effectiveness of the proposed approach for positioning improvement in GPS navigation processing.
维普期刊数据库