After analyzing the model of high dynamic signals, a quasi-open-loop carrier tracking method based on unscented Kalman filter (UKF) is proposed.
在分析高动态载波信号模型的基础上，提出了一种基于无迹卡尔曼滤波(ukf)的准开环载波跟踪方法。
Unscented Kalman filter(UKF) is a new nonlinear filtering method which does not linearize the equations thus avoiding the error due to the linearization.
不敏卡尔曼滤波（UKF）是一种新的非线性滤波的方法，它能减少线性化截断误差对系统定位精度的影响。
The state estimations algorithm for Target tracking have been studied and compared such as Kalman filter, Extented Kalman filter and Unscented Kalman filter.
对经典的卡尔曼滤波以及针对非线性系统的扩展卡尔曼滤波，不敏卡尔曼滤波算法进行了分析比较。
Unscented Kalman Filter (UKF), which is an evolutional algorithm of Extended Kalman Filter (EKF), has been successfully applied in many nonlinear estimation problems.
无轨迹卡尔曼滤波器(ukf)作为扩展卡尔曼滤波器(ekf)的进化算法在许多非线性估计问题上取得了成功的应用。
For satellite formation flying orbit adjustment situation, which only used radio measurement, a strong tracking unscented Kalman filter (UKF) algorithm was introduced to the simulation.
并针对编队卫星进行轨道机动时仅采用无线电进行测量的工况，采用强跟踪离散卡尔曼滤波(ukf)算法进行仿真计算。
Then the float ambiguity resolution was passed into an unscented Kalman filter as initial state value. UKF estimated the precise ambiguity resolution in real time with the initial value.
再以该近似解和协方差矩阵为初值，由无迹卡尔曼滤波(ukf)实时估计双差整周模糊度的精确解。
System observability matrix was derived, and the degree of observability was calculated. Relative motion states of non-cooperative space target were estimated through unscented Kalman filter (UKF).
通过计算系统可观测度和采用无迹卡尔曼滤波(ukf)对目标相对运动状态进行估计，研究了观测矢量方向和数量与相对导航精度的关系。
The kalman filter algorithm under hybrid coordinate and unscented transformation (UT) algorithm are investigated.
研究了混合坐标系下的卡尔曼滤波算法和采样变换(UT)算法。
The kalman filter algorithm under hybrid coordinate and unscented transformation (UT) algorithm are investigated.
研究了混合坐标系下的卡尔曼滤波算法和采样变换(UT)算法。
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