Parameter Estimation of Low-Frequency Signal with Negative Frequency Contribution

2013 ◽  
Vol 380-384 ◽  
pp. 3457-3460 ◽  
Author(s):  
Si Wei Tan ◽  
Zhi Liang Ren ◽  
Jiong Sun
Keyword(s):  
Parameter Estimation ◽  
Phase Difference ◽  
Spectrum Analysis ◽  
Low Frequency ◽  
High Accuracy ◽  
Signal Parameter ◽  
Frequency Signal ◽  
Spectrum Method ◽  
Analysis Theory ◽  
Simulation Results

According to the problem that there is a decline in accuracy of low-frequency signal parameter estimation by using the algorithm of all-phase FFT, an improved phase difference correcting spectrum method based on all-phase FFT is proposed. The contribution of negative frequency to FFT calculation was considered while using phase difference correcting spectrum method. The all-phase FFT spectrum analysis theory was presented as well as a traditional phase difference correcting method based on it. The equations of parameter estimation such as frequency, amplitude and phase for low-frequency signals were derived with the negative frequency contribution to spectrum analysis. The simulation results show that the method proposed in this paper can be used to estimate the parameters of low-frequency signals in a high accuracy, and also achieves an improvement in anti-noise ability.

scholarly journals Low frequency signal spectrum analysis for strong earthquakes

2012 ◽  
Vol 55 (1) ◽  
Author(s):  
Alexander Rozhnoi ◽  
Maria Solovieva ◽  
Pier Francesco Biagi ◽  
Konrad Schwingenschuh ◽  
Masashi Hayakawa
Keyword(s):  
Spectrum Analysis ◽  
Low Frequency ◽  
Signal Spectrum ◽  
Frequency Signal ◽  
Strong Earthquakes

scholarly journals Parameter Estimation of Photovoltaic Models via Cuckoo Search

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jieming Ma ◽  
T. O. Ting ◽  
Ka Lok Man ◽  
Nan Zhang ◽  
Sheng-Uei Guan ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Mean Squared Error ◽  
Estimation Method ◽  
Cuckoo Search ◽  
High Accuracy ◽  
Flight Behavior ◽  
Squared Error ◽  
Simulation Results ◽  
Bioinspired Algorithms ◽  
Significant Attention

Since conventional methods are incapable of estimating the parameters of Photovoltaic (PV) models with high accuracy, bioinspired algorithms have attracted significant attention in the last decade. Cuckoo Search (CS) is invented based on the inspiration of brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior. In this paper, a CS-based parameter estimation method is proposed to extract the parameters of single-diode models for commercial PV generators. Simulation results and experimental data show that the CS algorithm is capable of obtaining all the parameters with extremely high accuracy, depicted by a low Root-Mean-Squared-Error (RMSE) value. The proposed method outperforms other algorithms applied in this study.

Altering Spectrum Method in Temperature Measurement Using Infrared Imager in Complex Background Environment

2012 ◽  
Vol 479-481 ◽  
pp. 348-351 ◽  
Author(s):  
Zhen Yang ◽  
Shi Cheng Zhang ◽  
Li Yang
Keyword(s):  
Temperature Measurement ◽  
Background Radiation ◽  
High Accuracy ◽  
Measured Object ◽  
Spectrum Method ◽  
Complex Background ◽  
Infrared Imager ◽  
Iterative Equations ◽  
Infrared Temperature Measurement ◽  
Simulation Results

To improve the accuracy of temperature measurement using infrared imager in complex background environment, based on the principles and the formulas of temperature measurement using infrared imager, altering spectrum method in the infrared temperature measurement was derived. For the temperature measurement of gray body in complex background environment, three response bands should be selected in temperature measurement, and then the surface temperature could be obtained by solving responding two iterative equations. This method could be achieved technologically by two means: setting filters in front of infrared imager, or using infrared imagers with different bands. The simulation results show that the temperature of measured object could be obtained with high accuracy through the method, and its error is very small. Through this method, the temperature of measured object could be obtained without knowing its emissivity and background radiation, so the error caused by the measurement of the emissivity of measured object and background radiation could be reduced.

A Low Frequency and High-Precision Microbarograph Monitoring System

2012 ◽  
Vol 605-607 ◽  
pp. 873-877
Author(s):  
Lei Li ◽  
Zhong Hai Zhou ◽  
Cheng Xing Lv ◽  
Bo Liu ◽  
He Chao Zang ◽  
...  
Keyword(s):  
Monitoring System ◽  
High Precision ◽  
Measurement Accuracy ◽  
Dynamic Range ◽  
Low Frequency ◽  
Type A ◽  
High Accuracy ◽  
Signal Modulation ◽  
Frequency Signal ◽  
Wide Dynamic Range

A low frequency and high-precision microbarograph monitoring system is developed based on the Michelson interference of unequal-arm type, a method of signal modulation and compensation is presented, it improves the system’s anti-jamming capability and measurement accuracy. Experiments show that the monitoring system has a high accuracy and a wide dynamic range, especially for monitoring low-frequency signal.

Performance Analysis of LFM Signal Parameter Estimation through FrFT Transform

2012 ◽  
Vol 195-196 ◽  
pp. 80-83
Author(s):  
Ze Zhong Wang ◽  
Yu Huang ◽  
Feng Liu
Keyword(s):  
Fourier Transform ◽  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Frequency Estimation ◽  
Parameters Estimation ◽  
Chirp Rate ◽  
Signal Parameter ◽  
Central Frequency ◽  
Simulation Results ◽  
Radar Signals

The fractional Fourier transform (FrFT) used to process linearly frequency modulated (LFM) signals is applied in the differentiation and parameters estimation of LFM radar signals. The performance of the LFM signals detection and parameters estimation through FrFT are studied when the signal-noise ratio (SNR) is low. The situation is set and the demonstration routine through simulations is made so that the performance on the chirp rate estimation and the central frequency estimation of LFM signals through FrFT is tested, the time used to obtain parameter estimation results through computer simulations is compared. The simulation results demonstrate that the method through FrFT could be used to differentiate LFM radar signals and to estimate parameters of LFM radar signals when the SNR is low.

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