ID 原文 译文
26165 最后，通过一个算例验证了方法的有效性。 Finally, the effectiveness of the method is verified by a numerical example.
26166 针对贮存期光纤惯组性能检测问题，提出基于先验信息的静态检测方法。 To imu performance detection problem of storage period the fiber, static detection method based on prior information is put forward.
26167 该方案建立了光纤惯组检测用简化误差模型，引入零速信息和方位瞄准信息进行基于卡尔曼滤波对准的光纤惯组静态性能检测，并结合历史的检测信息进行比对。 The scheme fiber imu testing using simplified error model is established, the introduction of zero speed information based on kalman filter and azimuth aiming at information on optical fiber imu static performance test, combined with the history of information.
26168 通过该方法可检测出3个轴向陀螺和加速度计的等效零位误差，简化了惯组检测流程，缩短了检测时间。 By this method can detect three axial equivalent zero error of gyroscope and accelerometer, the simplified imu testing process, shorten the testing time.
26169 理论分析和仿真结果验证了该方案的可行性和正确性。 Theoretical analysis and simulation results verify the correctness and feasibility of the scheme.
26170 以单位四元数作为姿态描述参数提出一种乘性约束姿态估计算法。 By unit quaternion as a gesture description parameter a multiplicative constraints attitude estimation algorithm.
26171 四元数具有全局非奇异、运动学方程双线性的优点，但归一化约束条件必须精确保持。 Quaternions with global advantages of non singular bilinear, kinematics equation, but the normalized constraints must maintain accurate.
26172 首先，比较了加性和乘性滤波算法在估计误差定义和校正方式上的差别，并从物理概念和估计精度上详细分析了无约束四元数估计算法的不足。 First of all, the comparison of the additive and multiplicative algorithm defined in estimation error and correction of the difference on the way, from the physical concept and the estimation precision and unrestrained quaternion estimation algorithm is a detailed analysis.
26173 然后，针对"矢量测量+陀螺"姿态观测模式，利用乘性约束滤波算法设计了姿态估计器。 Then, in view of the "vector measurement + gyro attitude observation model, using the multiplicative constraints filtering algorithm attitude estimator is designed.
26174 针对状态部分受约束的姿态估计问题，推导了状态和方差预测方程及状态受约束的最优增益矩阵，并将约束增益矩阵应用到姿态估计算法的测量更新过程。 Some state controlled pose estimation problem, status and variance prediction equation was deduced and state constrained optimal gain matrix, and restricts the gain matrix is applied to the attitude estimation algorithm to measure the update process.