During a transfer alignment of strapdown inertial navigation system, Kalman filter models are linear time varying system whose analysis of observability is difficult.
捷联惯导系统的卡尔曼滤波模型在传递对准时，为线性时变系统，而线性时变系统的可观测性分析比较困难。
Accurate models and noise statistics are required in many tracking algorithms based on the traditional Kalman filter, which are difficult to be satisfied in engineering application.
在以常规卡尔曼滤波器为基础的各种跟踪算法中，要求精确的模型和噪声统计，但在实际问题中，大多数情况上述要求不能满足。
Kalman filter of the kind of equations was calculated with T-SFIMMA algorithm based on adaptive Kalman filter algorithm of T-S fuzzy model, realize the tracking and automatic switchover of models.
对各方程序卡尔曼滤波，通过T -SFIMMA算法进行基于T - S模糊模型的自适应卡尔曼滤波计算，实现系统模型的实时跟踪与自动转换。
In chapter 3, the orbit dynamics models are established, the Kalman Filter of the GPS and kinematics equation combined are designed, and simulations of different orbit Micro-satellite are done.
第三章，建立了卫星轨道动力学模型，设计了GPS和运动方程组合的卡尔曼滤波器，并针对不同轨道高度的微小卫星进行了定位仿真。
It introduces many kinds of speed observe models especially, then selects the speed estimation scheme based Kalman filter after comparing a great deal of schemes of distinguishing rotational speed.
重点介绍多种速度观测模型，并在比较诸多速度辨识方案后，采用基于卡尔曼滤波的速度估计方案。
It introduces many kinds of speed observe models especially, then selects the speed estimation scheme based Kalman filter after comparing a great deal of schemes of distinguishing rotational speed.
重点介绍多种速度观测模型，并在比较诸多速度辨识方案后，采用基于卡尔曼滤波的速度估计方案。
应用推荐