Accurate Damping Factor and Frequency Estimation for Damped Real-Valued Sinusoidal Signals

The interpolated discrete Fourier transform (IpDFT) is one of the most popular techniques to estimate the parameters of a damped real-valued sinusoidal signal (DRSS). However, its accuracy is affected by strong noise presence and short observation windows. To this end, this letter proposes a novel two-point IpDFT method, called I2pZDFT, for the parameter estimation of a DRSS. The proposed I2pZDFT uses the zero-padding technique to increase the sampling rate in the frequency domain. The conjugate symmetry and the parity of the zero-padded signal are utilized to eliminate the influence of the spectral leakage. Simulation results highlight that the proposed I2pZDFT outperforms the existing IpDFT-based methods in terms of noise immunity, especially in the case of observation windows as short as 0.5-1 cycles

Pulsar timing analysis in the presence of correlated noise

Pulsar timing observations are usually analysed with least-square-fitting procedures under the assumption that the timing residuals are uncorrelated (statistically "white"). Pulsar observers are well aware that this assumption often breaks down and causes severe errors in estimating the parameters of the timing model and their uncertainties. Ad hoc methods for minimizing these errors have been developed, but we show that they are far from optimal. Compensation for temporal correlation can be done optimally if the covariance matrix of the residuals is known using a linear transformation that whitens both the residuals and the timing model. We adopt a transformation based on the Cholesky decomposition of the covariance matrix, but the transformation is not unique. We show how to estimate the covariance matrix with sufficient accuracy to optimize the pulsar timing analysis. We also show how to apply this procedure to estimate the spectrum of any time series with a steep red power-law spectrum, including those with irregular sampling and variable error bars, which are otherwise very difficult to analyse.Comment: Accepted by MNRA

Power Harmonic Analysis Based on Continuously Adjustable Asymmetric Window

The study of harmonics signal analysis in electric power system is a classic and important research subject. The signal by using traditional Fourier transform methods are nearly truncated by constant coefficient symmetry window or asymmetric window. This paper propose the improved continuously adjustable asymmetric window for precise harmonic parameters measurement and the uniform formulas for calculating the parameters of harmonics and interharmonic is obtained by the asymmetric window-based phase difference correction method. The major advantages of this method is easy to implement and independent of window spectrum. The simulation analysis results proves that there is obvious high precision, effectiveness and universal applicability of this method

Synchrophasor Assisted Efficient Fault Location Techniques In An Active Distribution Network

Reliability of an electrical system can be improved by an efficient fault location identification for the fast repair and remedial actions. This scenario changes when there are large penetrations of distributed generation (DG) which makes the distribution system an active distribution system. An efficient use of synchrophasors in the distribution network is studied with bidirectional power flow, harmonics and low angle difference consideration which are not prevalent in a transmission network. A synchrophasor estimation algorithm for the P class PMU is developed and applied to identify efficient fault location. A fault location technique using two ended synchronized measurement is derived from the principle of transmission line settings to work in a distribution network which is independent of line parameters. The distribution systems have less line length, harmonics and different sized line conductors, which affects the sensitivity of the synchronized measurements, Total Vector Error (TVE) and threshold for angular separation between different points in the network. A new signal processing method based on Discrete Fourier Transform (DFT) is utilized to work in a distribution network as specified in IEEE C37.118 (2011) standard for synchrophasor. A specific P and M classes of synchrophasor measurements are defined in the standard. A tradeoff between fast acting P class and detailed measurement M class is sought to work specifically in the distribution system settings which is subjected to large amount of penetrations from the renewable energy

OFDM LOW COMPLEXITY CHANNEL ESTIMATION USING TIME-FREQUENCY ADJUSTABLE WINDOW FUNCTIONS

In this paper, we introduce a low complexity algorithm for estimation of the channel transfer function in the OFDM communication system that is using a scattered pilot symbol grid. Although, the use of the scattered pilot grid enables implementation of the flexible, and adaptive radio interface, it suffers from a high estimation error at the edges of the symbol sequence. Due to the sampling in time, and frequency, the signal is circularly expanded in both domains, and this has to be taken into account when the signal is processed. The proposed algorithm is shaping the pilot symbol estimates in time, and frequency domain, such that the aliasing in both domains are reduced or eliminated. We achieve a significant reduction of the estimation error, with a linear increase in computational complexity

Demodulation of Spatial Carrier Images: Performance Analysis of Several Algorithms Using a Single Image

http://link.springer.com/article/10.1007%2Fs11340-013-9741-6#Optical full-field techniques have a great importance in modern experimental mechanics. Even if they are reasonably spread among the university laboratories, their diffusion in industrial companies remains very narrow for several reasons, especially a lack of metrological performance assessment. A full-field measurement can be characterized by its resolution, bias, measuring range, and by a specific quantity, the spatial resolution. The present paper proposes an original procedure to estimate in one single step the resolution, bias and spatial resolution for a given operator (decoding algorithms such as image correlation, low-pass filters, derivation tools ...). This procedure is based on the construction of a particular multi-frequential field, and a Bode diagram representation of the results. This analysis is applied to various phase demodulating algorithms suited to estimate in-plane displacements.GDR CNRS 2519 “Mesures de Champs et Identification en Mécanique des Solide

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada

Spectral correction method based on improved flat-top convoluted window for parameter estimation of power harmonic

Točna procjena harmonijskog parametra je važan zadatak u obradi signala elektroenergetskog sustava. Predlaže se nova vrsta flat-top prozora koja se generira vlastitim konvolucijama brzo padajućeg flat-top prozora (FDMS-FT) u domenu vremena. Proučavaju se značajke bočnog i glavnog režnja novog prozora. Nadalje, kako bi se poboljšala glatkoća glavnog režnja novog prozora, optimiziraju se koeficijenti matičnog prozora. Predstavlja se izmjenjivi algoritam ispravke razlike faze duljine prozora baziran na novom prozoru kako bi se procijenio strujni harmonični parametar. Kako bi se provjerila učinkovitost i točnost prikazane metode, provedeno je nekoliko računalnih simulacija i praktičnih eksperimenata s višefrekvencijskim strujnim signalima. Rezultati pokazuju da predložena metoda može učinkovito smanjiti opseg računanja i daje visok parametar točnosti procjene harmonijske snage.Accurate estimation of harmonic parameter is an important task in signal processing of power system. A new class of flat-top windows is proposed, which is generated by self-convolutions of the fast-decaying minimum-sidelobe flat-top (FDMS-FT) window in the time-domain. The mainlobe and sidelobe features of the new window are studied. In addition, to improve the flatness of mainlobe of the new window, the coefficients of its parent window are optimized. A window-length changeable discrete phase difference correction algorithm based on the new window is presented to estimate power harmonic parameter. In order to inspect the efficiency and accuracy of the presented method, several computer simulations and practical experiments were conducted with power multi-frequency signals. Results show that the proposed method can reduce the computation load efficiently and gives a high parameter estimation accuracy of power harmonic

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada