scholarly journals Barycenter Theorem in Phase Characteristics of Symmetric and Asymmetric Windows

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 329
Author(s):  
Jiufei Luo ◽  
Haitao Xu ◽  
Kai Zheng ◽  
Xinyi Li ◽  
Song Feng
Keyword(s):  
Frequency Estimation ◽  
Random Noise ◽  
Estimation Algorithm ◽  
Frequency Component ◽  
Phase Response ◽  
Numeric Simulation ◽  
Simulation Results ◽  
The Time Domain ◽  
Short Time ◽  
The Relationship

Asymmetric windows are of increasing interest to researchers because of the nonlinear and adjustable phase response, as well as alterable time delay. Short-time phase distortion can provide an essential improvement in speech coding, and also has better performance in speech recognition. The merits of asymmetric windows in the aspect of spectral behaviors have an important function in frequency component detection and parameter estimation. In this paper, the phase response of windows were further studied, and the phase characteristics of symmetric and asymmetric windows are described. The relationship between the barycenter of windows in the time domain, and the phase characteristic at the center of the main lobe in the frequency domain, was established. In light of the relationship, an improved version of the asymmetric window- based frequency estimation algorithm was proposed. The improved algorithm has advantages of straightforward implementation and computational efficiency. The numeric simulation results also indicate that the improved approach is more robust than the traditional method against additive random noise.

scholarly journals DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3043 ◽  
Author(s):  
Weike Zhang ◽  
Xi Chen ◽  
Kaibo Cui ◽  
Tao Xie ◽  
Naichang Yuan
Keyword(s):  
Linear Array ◽  
Estimation Algorithm ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Angle Measurement ◽  
Lookup Table ◽  
Signal Parameters ◽  
Estimation Precision ◽  
Simulation Results ◽  
The Relationship

In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm.

scholarly journals Frequency estimators with high resistance to interference from image frequency components

2018 ◽  
Vol 12 (2) ◽  
pp. 147-158 ◽  
Author(s):  
Wei Zhou ◽  
Liqun Gan ◽  
Hong Xiao ◽  
Yi Zhang ◽  
Haitao Xu ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Frequency Estimation ◽  
Geometric Mean ◽  
Random Noise ◽  
Estimation Algorithm ◽  
Side Lobe ◽  
Sine Wave ◽  
Practical Engineering ◽  
Frequency Components ◽  
Image Frequency

This paper presents an improved frequency estimation algorithm based on the interpolated discrete Fourier transform. High-accurate frequency estimation can be achieved by taking the geometric mean of two independent estimates, which are derived from the real parts of the two largest spectral bins and the imaginary parts, respectively. In situations where only a small number of sine wave cycles are observed, the ability of the algorithm to cancel interference from image frequency components results in improvements in accuracy. The residual errors of the proposed algorithm have been theoretically analyzed with maximum side-lobe decaying windows, since the windows have simple and uniform analytical expression of interpolation algorithm. The performance of the proposed algorithm was investigated using both Hanning and three-term maximum side-lobe decaying windows. A comparative analysis of systematic errors and noise sensitivity was performed between the new algorithm and traditional algorithms. Both the root mean squared error and the probability density of the errors were investigated under noisy conditions. Simulation results demonstrated that the new algorithm is not only highly resistant to interference from image components but is also resistant to the effects of random noise. The results presented in the paper are useful for identifying the best choice of algorithm in practical engineering applications.

scholarly journals A new spectrum feature discovered for a category of signals produced by massive and random micro-sources

2018 ◽  
Vol 210 ◽  
pp. 05010
Author(s):  
Xiaodong Zhuang ◽  
Nikos Mastorakis
Keyword(s):  
Statistical Study ◽  
Amplitude Spectrum ◽  
Time Spectrum ◽  
Frequency Component ◽  
Main Category ◽  
Frequency Components ◽  
Spectrum Feature ◽  
Short Time ◽  
The Relationship ◽  
System Characteristics

A statistical study is implemented on the short-time spectrum of one main category of random signals. For the signals with massive and random micro-sources, a new statistic feature of the short-time amplitude spectrum is discovered, which reveals the relationship between the amplitude’s average and its standard for each frequency component. Moreover, the association between the amplitude distributions for different frequency components is also studied. A model representing such association is presented, which accords well with the statistic feature discovered. The analysis result has potential application in signal classification, and also in the study of system characteristics underlying the observed signal.

ADAPTIVE FREQUENCY ESTIMATION WITH LOW SAMPLING RATES BASED ON ROBUST CHINESE REMAINDER THEOREM AND IIR NOTCH FILTER

2009 ◽  
Vol 01 (04) ◽  
pp. 587-600
Author(s):  
HONG LIANG ◽  
XIAOWEI LI ◽  
XIANG-GEN XIA
Keyword(s):  
Chinese Remainder Theorem ◽  
Frequency Estimation ◽  
Notch Filter ◽  
Estimation Algorithm ◽  
Nonstationary Signals ◽  
Simulation Results ◽  
Sinusoidal Signals ◽  
Present Simulation

In this paper, based on an adaptive IIR notch filter and a robust Chinese remainder theorem (CRT), we propose an adaptive frequency estimation algorithm from multiple undersampled sinusoidal signals. Our proposed algorithm can significantly reduce the sampling rates and provide more accurate estimates than the method based on adaptive IIR notch filter and sampling rates above the Nyquist rates does. We then present simulation results to verify the performance of our proposed algorithm for both stationary and nonstationary signals.

scholarly journals Joint Angle and Frequency Estimation Using One-Bit Measurements

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5422 ◽  
Author(s):  
Zeyang Li ◽  
Junpeng Shi ◽  
Xinhai Wang ◽  
Fangqing Wen
Keyword(s):  
Factor Analysis ◽  
Array Signal Processing ◽  
Joint Angle ◽  
Frequency Estimation ◽  
Sensor Arrays ◽  
Covariance Matrices ◽  
Parallel Factor ◽  
Simulation Results ◽  
The Relationship ◽  
Important Branch

Joint angle and frequency estimation is an important branch in array signal processing with numerous applications in radar, sonar, wireless communications, etc. Extensive attention has been paid and numerous algorithms have been developed. However, existing algorithms rely on accurately quantified measurements. In this paper, we stress the problem of angle and frequency estimation for sensor arrays using one-bit measurements. The relationship between the covariance matrices of one-bit measurement and that of the accurately quantified measurement is extended to the tensor domain. Moreover, a one-bit parallel factor analysis (PARAFAC) estimator is proposed. The simulation results show that the angle and frequency estimation can be quickly achieved and correctly paired.

A Correlation Coefficient Estimation Algorithm Based on Subspace Decomposition

2014 ◽  
Vol 989-994 ◽  
pp. 1883-1886
Author(s):  
Na Wu ◽  
Wei Jian Si ◽  
Shu Hong Jiao
Keyword(s):  
Covariance Matrix ◽  
Correlation Coefficient ◽  
Estimation Algorithm ◽  
Signal Subspace ◽  
Subspace Decomposition ◽  
Coefficient Estimation ◽  
Eigen Value ◽  
Simulation Results ◽  
Value Decomposition ◽  
The Relationship

the correlation coefficient estimation algorithm based on subspace decomposition is presented in this paper. The correlation coefficient between the signals is obtained by getting eigen-value decomposition of the data covariance matrix, and deriving the relationship between signal subspace and noise subspace. Simulation results verify that this algorithm can be realized to get the correlation coefficient between two incident signals whose DOA are known and the effect of the correlation coefficient estimation is made by different signal direction angular intervals.

scholarly journals Ultrasonic Assessment of Thickness and Bonding Quality of Coating Layer Based on Short-Time Fourier Transform and Convolutional Neural Networks

Coatings ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 909
Author(s):  
Azamatjon Kakhramon ugli Malikov ◽  
Younho Cho ◽  
Young H. Kim ◽  
Jeongnam Kim ◽  
Junpil Park ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Coating Layer ◽  
Ultrasonic Pulse ◽  
Short Time Fourier Transform ◽  
Coating Materials ◽  
Time Frequency ◽  
High Attenuation ◽  
Bonding State ◽  
The Time Domain ◽  
Short Time

Ultrasonic non-destructive analysis is a promising and effective method for the inspection of protective coating materials. Offshore coating exhibits a high attenuation rate of ultrasonic energy due to the absorption and ultrasonic pulse echo testing becomes difficult due to the small amplitude of the second echo from the back wall of the coating layer. In order to address these problems, an advanced ultrasonic signal analysis has been proposed. An ultrasonic delay line was applied due to the high attenuation of the coating layer. A short-time Fourier transform (STFT) of the waveform was implemented to measure the thickness and state of bonding of coating materials. The thickness of the coating material was estimated by the projection of the STFT into the time-domain. The bonding and debonding of the coating layers were distinguished using the ratio of the STFT magnitude peaks of the two subsequent wave echoes. In addition, the advantage of the STFT-based approach is that it can accurately and quickly estimate the time of flight (TOF) of a signal even at low signal-to-noise ratios. Finally, a convolutional neural network (CNN) was applied to automatically determine the bonding state of the coatings. The time–frequency representation of the waveform was used as the input to the CNN. The experimental results demonstrated that the proposed method automatically determines the bonding state of the coatings with high accuracy. The present approach is more efficient compared to the method of estimating bonding state using attenuation.

Optimized Mooring Line Simulation Using a Hybrid Method Time Domain Scheme

2014 ◽  
Author(s):  
Niels Hørbye Christiansen ◽  
Per Erlend Torbergsen Voie ◽  
Jan Høgsberg ◽  
Nils Sødahl
Keyword(s):  
Hybrid Method ◽  
Time Domain ◽  
Computation Time ◽  
Mooring Line ◽  
Mooring Lines ◽  
Fem Model ◽  
Input Variables ◽  
The Time Domain ◽  
The Cost ◽  
Short Time

Dynamic analyses of slender marine structures are computationally expensive. Recently it has been shown how a hybrid method which combines FEM models and artificial neural networks (ANN) can be used to reduce the computation time spend on the time domain simulations associated with fatigue analysis of mooring lines by two orders of magnitude. The present study shows how an ANN trained to perform nonlinear dynamic response simulation can be optimized using a method known as optimal brain damage (OBD) and thereby be used to rank the importance of all analysis input. Both the training and the optimization of the ANN are based on one short time domain simulation sequence generated by a FEM model of the structure. This means that it is possible to evaluate the importance of input parameters based on this single simulation only. The method is tested on a numerical model of mooring lines on a floating off-shore installation. It is shown that it is possible to estimate the cost of ignoring one or more input variables in an analysis.

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