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 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) 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。
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