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- The Unscented Kalman Filter (UKF) is a novel development in the field. Then, pr (译)：的Unscented卡尔曼滤波（ UKF方法）是一种新的发展领域。
- A new method is proposed for training radial basis function networks (RBFN) using the unscented Kalman filter (UKF). 摘要提出了应用无先导卡尔曼滤波器(UKF)来训练径向基神经网络(RBFN)的新方法。
- An Unscented Kalman Filter (UKF) based noncoherent detection method for Chaos-Shift-Keying (CSK) communication system is proposed in this paper. 基于UKF算法，该文提出一种CSK通信系统的非相干检测方法。
- To handle nonlinearity, unscented kalman filter is introduced into the design of the elemental filter that is hypothesis dependent. 为有效处理非线性，不敏卡尔曼滤波器被用于设计依赖假设的单元滤波器。
- An algorithm based on square root unscented Kalman filter (SRUKF) was presented to solve the aeroengine health parameter estimation problem. 摘要设计了适用于双轴涡扇发动机健康参数估计的平方根UKF滤波算法，解决了线性片尔曼滤波器估计结果准确性依赖于线性模型精度；
- Abstract A new method is proposed for training radial basis function networks (RBFN) using the unscented Kalman filter (UKF). 摘要 提出了应用无先导卡尔曼滤波器（UKF）来训练径向基神经网络（RBFN）的新方法。
- The performances of the extended kalman filter(EKF) and the unscented kalman filter(UKF)in constant velocity(CV) model are compared. 比较了跟踪系统中扩展卡尔曼滤波、无迹滤波在二阶常速(CV)统计模型下实现的性能。
- The superior performance of the improved unscented kalman filter (UKF) is clearly shown in a numerical example compared with the standard one.The new method has the great ... 仿真结果表明,该算法适用于系统含有未知输入或系统噪声为非高斯的情况,并可解决一些典型的非线性估计问题,改进算法的性能优于传统无迹滤波器。
- Then we studied the tracking problem of multiple maneuvering targets by using the combination of interacting multi-model and unscented Kalman filter algorithm. 在此基础上,采用交互式多模型算法和无味卡尔曼滤波相结合的方法研究了多机动目标的跟踪问题。
- A new method for training RBFN named “Unscented Kalman Filter” (UKF) through a mass of academic analysis based on the optimization was proposed instead. 在大量的理论分析以及实际仿真的基础上，我们提出了一种新的用于RBFN训练的算法-无先导卡尔曼滤波器（UKF）算法。
- In order to improve the positioning precision and reliability,extended Kalman filter(EKF),particle filter(PF) and unscented Kalman filter(UKF) algorithms were analyzed respectively. 为了提高组合导航定位系统的定位精度和可靠性,分别对扩展卡尔曼滤波(EKF)、粒子滤波(PF)和U卡尔曼滤波(UKF)3种算法进行了分析。
- The first approach is based on the unscented Kalman filtering (UKF).Its premise and characteristics for integrated navigation system are presented. 本文第二部分研究了对导航多传感器的非线性信息融合方法。
- This algorithm adopts the weight control parameter to decide whether the particle enters unscented Kalman filter, thus decreasing filtering computing amount and having the same precision of UPF. 该算法采用权值控制参数决定粒子是否进入平淡卡尔曼滤波器，有效降低了滤波计算量，并和UPF算法精度相当。
- feedback unscented Kalman filter 反馈型无先导卡尔曼滤波器
- IUKF(Iterated Unscented Kalman Filter) 迭代采样卡尔曼滤波
- square root Unscented Kalman filter 平方根Unscented卡尔曼滤波
- square-root unscented Kalman filter 平方根UKF
- The advances of unscented Kalman filter (UKF) are firstly reviewed.The combination of the Kalman linear filtering with the unscented transformation (UT) is discussed in general sense. 摘要回顾了UKF算法的发展，从一般意义讨论了UT变换算法和采样策略的选择依据，并给出了UKF算法描述。
- adaptive unscented Kalman filter 自适应无迹滤波器
- federated Unscented Kalman Filtering 联邦UKF
