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Iterative Frequency Estimation Based on MVDR Spectrum
DOI:10.1109/TPWRD.2009.2031116.png)
摘要
En 中文
Frequency estimation is an important task in a power system since the frequency deviation is a yardstick for the power system abnormal operating conditions. This paper presents a new frequency-estimation algorithm based on the minimum variance distortionless response spectrum that has advantages of accuracy, fast convergence, and modest complexity. To reduce complexity without a trade off of accuracy, an iterative searching method is introduced. An adaptive step-size method is also introduced to reduce gradient noise. Complexity of the proposed algorithm is O(K) or O(K-2) depending on environments where is the dimension of correlation matrix. When compared with other conventional adaptive algorithms, simulation results show that the proposed algorithm improves convergence speed, and has lower frequency estimation error in cases of high signal-to-noise ratio.
Keyword:
Adaptive step size
frequency estimation
iterative method
minimum variance distortionless response (MVDR) spectrum
期刊
IF:
3.7
论文数:
9.1K
被引数:
2.2W
机构
引用论文
A novel Kalman filter for frequency estimation of distorted signals in power systems一种用于电力系统失真信号频率估计的新型卡尔曼滤波器
Frequency estimation of distorted power system signals using extended complex Kalman filters基于扩展复数卡尔曼滤波器的畸变电力系统信号频率估计

