For improving the locating accuracy, the EKF algorithm is introduced to process the initial locating results.
为了提高定位精度，本文又引入扩展卡尔曼滤波算法对原始定位结果进行处理。
The simulation results indicate that the variable cycle RP-EKF algorithm can resolve the filtering instability of EKF for the bearing-only target tracking and the time-delay problem.
仿真结果表明变周期距离参数化扩展卡尔曼滤波算法能有效解决经典扩展卡尔曼滤波算法在纯方位角目标跟踪时可能出现的滤波发散现象，并能处理声音信号的传输时间延迟问题。
Two different Monte Carlo simulations show that the new algorithm cannot only improve state estimation accuracy but also is superior to EKF in estimation performance and computation efficiency.
两个不同的蒙特卡罗仿真表明，通过采用这一新算法引人径向速度测量，不仅可以大大提高状态估计的精度，而且其估计性能和计算效率优于传统的EKF。
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。
Maneuvering target tracking algorithm based on adaptive Gauss model and EKF was built for improving the tracking performance in Multi-static systems.
为改善多基地雷达系统对高机动目标的跟踪性能，提出了基于自适应高斯模型和扩展卡尔曼滤波(ekf)的机动目标跟踪算法。
An extended Kalman filtering (EKF) algorithm is designed for radiolocation in cellular communication system, simulation is conducted to examine its performance.
设计了一种蜂窝系统无线定位中使用的扩展卡尔曼滤波(ekf)算法，对其性能进行了仿真。
According to the peculiarity of the SINS nonlinear error model, the simplified SPKF algorithm was derived, and the SINS initial alignment were simulated based on EKF and simplified SPKF.
针对对准模型的特性，推导了SPKF简化算法，进行了静基座下基于扩展卡尔曼滤波(ekf)、简化spkf的SINS初始对准仿真。
The dissertation researches on the PMSM vector control system using Extended Kalman Filtering (EKF) algorithm.
本文是对永磁同步电机的扩展卡尔曼无位置算法（EKF）的矢量控制系统的研究。
The research results of dynamic state estimation algorithm were introduced, which were EKF method, UKF method, predictive Kalman filtering and nonlinear predictive Kalman filtering.
简要分析了几种常见的动态估计方法，它们是EKF方法、UKF方法、预测卡尔曼滤波；
The research results of dynamic state estimation algorithm were introduced, which were EKF method, UKF method, predictive Kalman filtering and nonlinear predictive Kalman filtering.
简要分析了几种常见的动态估计方法，它们是EKF方法、UKF方法、预测卡尔曼滤波；
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