匹配信息丢失条件下传递对准方法研究

针对传递对准过程中匹配信息的丢失会导致对准滤波器的估计误差过大甚至发散的问题，提出了一种基于改进无迹卡尔曼滤波（UKF）方法的舰载传递对准方案. 该方法通过在滤波器的更新方程中设置一个控制变量，根据当前时刻是否存在匹配数据丢失的判断结果对滤波更新过程进行相应处理，并对所提对准算法的估计误差的有界性进行了分析. 在几种不同等级的匹配信息丢失率的情况下，所提出的方法均能够以较高精度完成对姿态失准角的估计. 仿真结果表明了该方法的有效性. 

Transfer Alignment Method Under Matching Data Dropout

In order to solve the problem of matching data dropout of transfer alignment which can cause big estimation error or divergence of the alignment filter, a ship-borne alignment method based on improved unscented Kalman filter (UKF) was proposed, in which a control variable that can adjust the filtering update process according to the situation of measurement data dropout was introduced. Under the proposed scheme, the boundedness of the estimation error can be guaranteed. Moreover, the new alignment method can acquire accurate estimate of attitude misalignment in the situations of different matching data dropout rates. Finally, the effectiveness is demonstrated by the simulation study.