Abstract: a new three-phase state estimation algorithm is proposed and its details are presented in this paper.
文摘：提出了一种新的三相状态估计算法，并详细地阐述了一种三相状态估计的处理策略。
A three phase distribution system state estimation algorithm is proposed in this paper which based on Newton method.
提出了一种基于牛顿法的三相配网状态估计算法。
The least absolute value state estimation algorithm is employed in this paper to identify the network topology errors.
这是识别负荷突变、拓扑错误和坏数据三者交叠问题的基础。
Therefore, state estimation algorithm based on the measurement transformation of the equivalent current is studied in this paper.
因此，本文对基于等效电流量测变换的电力系统状态估计算法进行了研究分析。
In the sense of linear unbiased minimum variance estimation, a global optimal recursive state estimation algorithm for this discretized linear system is proposed.
在线性无偏最小方差估计准则下，推导出了该离散化后所得系统的全局最优递推状态估计算法。
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；
To improve the accuracy of tracking the complex maneuver target in cluttered environment, a new state estimation algorithm based on the expectation maximization (EM) algorithm is presented.
为了提高在杂波环境下跟踪强机动目标的精度，提出了一种新的基于期望极大化(EM)算法的机动目标状态估计方法。
For the estimation of satellite state, the extended sequential estimation algorithm was applied. The numerical method was used to integrate state vector and error covariance matrix.
在卫星的状态估计过程中应用推广的序列估计算法，借助数值积分方法积分状态向量和协方差矩阵。
Based on linear unbiased minimum variance estimation theory, a fusion algorithm which fused the state vector of nonlinear systems with dissimilar sensors with arbitrary correlated noises is developed.
基于线性无偏最小方差估计理论，提出了一种任意相关噪声异类传感器非线性系统状态矢量融合算法。
This paper presents an algorithm for dynamic state estimation of power systems.
本文介绍了一种电力系统动态状态估计的算法。
Satisfactory results were achieved by using the extended Kalman filtering iterative algorithm for on-line state estimation.
用推广卡尔曼滤波迭代算法进行状态实时估计取得令人满意的结果。
The optimal estimation algorithm of measurement noise and the optimal state fusion algorithm for multi-channel system with multiplicative noises are mainly researched in this dissertation.
本文主要针对多通道带乘性噪声系统的观测噪声最优估计算法和状态最优融合估计算法展开进一步研究。
Additionally, the paper investigates the statistical characteristics of objective functions of harmonic state estimation problem and thus presents practical algorithm evaluating quality of estimation.
另外，文章调查了谐波状态估计问题的统计特性，并在此基础上提出了评价估计质量的具体算法。
The state equation and detecting equation of the position error of moving target are built, the location and track to moving target is achieved by least-square estimation and Kalman filter algorithm.
列出了对位置偏差估计的状态方程和测量方程，用加权的最小二乘估计和卡尔曼滤波算法，实现了定位和跟踪。
A new algorithm for state estimation based on the fast decoupling of distribution system's asymmetrical phases in phase coordinates is proposed.
提出了一种基于相坐标系的配电网三相不对称解耦的状态估计算法。
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。
If exact JSI was not available, however, an iteratively joint jammer state estimation and decoding algorithm was proposed.
同时，在无法得到精确干扰状态信息的情况下，提出了一种迭代干扰状态估计及译码算法。
There are two forms of extended sequential estimation algorithm: 1. integrating error covariance matrix; 2. integrating state transition matrix.
推广的序贯估算法有两种形式：1。积分误差协方差矩阵，2。积分状态转移矩阵。
Based on the linear unbiased minimum variance estimation theory, an asynchronous fusion algorithm that fused the state vector of linear system with arbitrary correlated noises is developed.
基于线性无偏最小方差估计理论，提出了一种任意相关噪声异类传感器非线性系统状态矢量融合算法。
A new observability analysis algorithm for power system state estimation based on reduced network Jacobian matrix is proposed.
提出了一种新的基于降阶网络雅可比矩阵的电力系统状态估计可观测性分析方法。
In this paper, the Householder orthogonal transform algorithm is used to solve the problems of power system state estimation.
本文提出用豪斯·霍尔德正交变换算法，求解电力系统的状态估计问题。
The problem of robust state estimation for continuous-time singular linear systems with un-certain noise is considered. A kind of practical algorithm of optimum recurrence estimation is obtained.
本文讨论了一类具有不确定噪声的连续广义线性系统的鲁棒状态估计问题，文章提供了一种比较实用的状态估计方法。
Secondly, based on state estimation in power system, establish equivalent model and the corresponding line estimation algorithm for any given transmission which need to be analysis.
其次，在电网状态估计基础上，建立针对任一输电线路载荷定值的在线估计等值模型和相应算法。
Based on Multi_sensor Multi_model information, we present a new algorithm based on total information fusion estimation on target state. We prove the validity of this algorithm by computer.
基于多传感器多模型信息，给出了目标状态基于全局信息融合估计的一种新算法，并通过计算机仿真验证了这种算法的有效性。
Based on the robust estimation in the state-space and the adaptive modification of prediction covariance matrix, a new algorithm was proposed to track Thevenin equivalent parameters.
融合预报协方差矩阵的自适应调整和状态空间鲁棒性估计，给出辨识戴维南等值参数的新算法。
Proposed algorithm can be used to establish models of state estimation process for steam coal blending.
我们以煤灰软化温度预测为例，介绍了如何将该算法应用于动力配煤过程的状态预测建模。
Proposed algorithm can be used to establish models of state estimation process for steam coal blending.
我们以煤灰软化温度预测为例，介绍了如何将该算法应用于动力配煤过程的状态预测建模。
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