提出了在三维空间中引入径向速度的非线性卡尔曼滤波算法。
Based on three-dimensional space, a new method for the nonlinear Kalman filter using the radial velocity is presented.
在作状态估计时，采用两组非线性卡尔曼滤波切换提高融合精度。
The exchange of two nonlinear Kalman filters was used to improve the fusion accuracy in the state estimation.
在非线性、非高斯条件下进行动基座传递对准，如果采用卡尔曼滤波会出现误差较大甚至发散的问题。
In moving base transfer alignment under nonlinear and non-Gaussian situation, using Kalman Filtering could cause large error or even divergence.
应用推荐