信息与控制2013，Vol.42Issue(2)：152-156,5.DOI:10.3724/SP.J.1219.2013.00152
一种GPS窄带干扰自适应卡尔曼滤波算法
An Adaptive Kalman Filtering Algorithm for Narrowband Interference on GPS
摘要
Abstract
For the narrowband interference on GPS, an auto-regressive (AR) model based adaptive Kalman filtering al gorithm is presented. The feasibility of the algorithm for nonstationary signal filtering is analyzed. With the swatch data, the state space model of system is built by taking the auto-regressive parameter as state vector. The parameter and the rank of auto-regressive model are estimated. The AR model based algorithm is used to process the GPS data. Compared with the recursive least square (RLS) and least mean square (LMS) algorithms, the adaptive filtering algorithm has lower filtering error and higher convergence speed.关键词
自回归模型/自适应卡尔曼滤波/窄带干扰/GPS/状态空间模型Key words
auto-regressive model/adaptive Kalman filtering/narrowband interference/GPS/state space model分类
信息技术与安全科学引用本文复制引用
张兰勇,刘繁明,李冰..一种GPS窄带干扰自适应卡尔曼滤波算法[J].信息与控制,2013,42(2):152-156,5.基金项目
国家自然科学基金资助项目(51079033) （51079033）
中央高校基本科研业务费资助项目(HEUCF110420,HEUCF110403,HEUCFR1210). （HEUCF110420,HEUCF110403,HEUCFR1210）
