因此，针对水下平台的晃动进行姿态预测与姿态补偿成为水下探测、定位的关键技术。
Therefore it is a crucial technique to predict and compensate the attitude of swaying platform.
结合矢量观测的特点，基于最小模型误差准则给出了一种确定卫星姿态的实时估计算法，称为预测滤波算法。
Considering the character of vector observation, a real time predictive filter based on minimum model error (MME) criterion is presented for satellite attitude estimation.
在确定卫星姿态确定的状态估计法中，经典的扩展卡尔曼滤波(ekf)和新提出的非线性预测滤波(NPF)这两种实时滤波算法各有优缺点。
In state estimation of satellite attitude determination, both traditional extended Kalman filter (EKF) and the proposed nonlinear predictive filter (NPF) have their own merits and defects.
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