所属单位：信息与控制工程学院

发表刊物：Discrete Dynamics in Nature and Society

关键字：中文关键字：角速度匹配;惯性导航系统;初始对准;传递对准;H滤波，英文关键字：Angular Rate Matching; Inertial Navigation System;

摘要：Inertial Navigation System (INS) must have the initial alignment before INS start work， because it is not confirmed the navigation coordinal of system. The precision of INS is usually determined by the precision of initial alignment. In the recently years, the more researcher pay more attention to study of the initial alignment, especially the initial alignment of INS on dynamical base. The Transfer Alignment (TA) scheme is used to the initial alignment of INS on dynamical base, because the TA is more suitable for the initial alignment of INS on dynamical base which is very complicated. The Kalman filter is often used in TA to improve the precision of TA. The statistical characteristics of interference signal and dynamic model of system must be known before the Kalman filter is used in the TA. But it is difficult to know the statistical characteristics of interference signal, because the interference signal is random signal and there are some changes on the dynamic model of system. Based on the uncertainty of the statistical characteristics of interference signal and dynamic model of system, the filter construct is used to guarantees the stability of matching filter and the accuracy of the TA. In this paper, the filter is adopted in the TA scheme of the angular rate matching when the various stages of disturbance in measurement are unknown. While the filter is compared with the Kalman filter in the same environment of simulation and evaluation. The result of simulation shows that the filter and the Kalman filter are both effective. But the Kalman filter is more accurate than the filter when system noise and measurement noise are white noise, while the filter is more accurate and quickly than the Kalman filter when system noise and measurement noise are color noise. In the engineering practice, system noise and measurement noise are always color noise ,so the filter is more suitable to engineering practice than the Kalman filter.

备注：宋丽君

第一作者：孙继武,段中兴,宋丽君

论文类型：期刊论文

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是否译文：否

发表时间：2016-04-01