Interpolation Algorithms of DFT for Parameters Estimation of Sinusoidal and Damped Sinusoidal Signals

Duda, Krzysztof

doi:10.5772/36264

Cited by 15 publications

(9 citation statements)

References 21 publications

(16 reference statements)

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“…In a real case the coherent frequency relationships between all the frequencies contained in the input signal and the sampling frequency are not met, leading to the well-known leakage phenomena. The way used to reduce this problem is called 'windowing' and a frequencydomain method often used for estimating the multifrequency signal parameters under noncoherent sampling is the Interpolated DFT (IpDFT) method [4][5]. This method provides very accurate parameter estimates, but requires a considerable amount of computation.…”

Section: Introductionmentioning

confidence: 99%

Algorithm for Simultaneous Parameter Estimation of A Multiharmonic Signal

Petrović¹

2012

Metrology and Measurement Systems

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Estimating the fundamental frequency and harmonic parameters is basic for signal modelling in a power supply system. Differing from the existing parameter estimation algorithms either in power quality monitoring or in harmonic compensation, the proposed algorithm enables a simultaneous estimation of the fundamental frequency, the amplitudes and phases of harmonic waves. A pure sinusoid is obtained from an input multiharmonic input signal by finite-impulse-response (FIR) comb filters. Proposed algorithm is based on the use of partial derivatives of the processed signal and the weighted estimation procedure to estimate the fundamental frequency, the amplitude and the phase of a multi-sinusoidal signal. The proposed algorithm can be applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The simulation results verify the effectiveness of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Algorithm for Simultaneous Parameter Estimation of A Multiharmonic Signal

Petrović¹

2012

Metrology and Measurement Systems

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“…The goal is to synchronize the sampling frequency of a measuring system to the frequency of a sine wave, generated by a low-distortion oscillator, using the estimation of the frequency offset given by (9). The accuracy of the estimation of the frequency offset is compared with the estimator obtained by the three-point interpolation algorithm (IpDFT) [23]. The effect of a small remaining frequency offset, δ, on the amplitude of the fundamental component will then be examined.…”

Section: Experimental Validationmentioning

confidence: 99%

“…4 shows the bias ( δ − δ) of this estimator for frequency offsets ranging from −100 μHz/Hz to 100 μHz/Hz. For comparison purpose, the bias of the estimator calculated by threepoint interpolation of DFT (IpDFT) [23] is also presented…”

Section: B Synchronizationmentioning

confidence: 99%

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Synchronization of Sampling-Based Measuring Systesm

Overney

Mortara

2014

IEEE Trans. Instrum. Meas.

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The amplitude and the phase of a measured singletone signal can accurately be calculated from the discrete Fourier transform (DFT) components in case of coherent sampling. When the synchronization is not perfect, spectral leakage appears and errors are introduced in the determination of the signal parameters. In this paper, a new method to synchronize the sampling frequency with the frequency of the measured signal is presented. The method is based on the information contained in the fundamental and the sideband components of the DFT of the measured signal. A single measurement gives the synchronization error and permits the correction of the sampling frequency required to become coherent. Moreover, the error on the amplitude measurement relative to a quasi-coherent sampling is also discussed and quantitatively modeled. The results of the model as well as the synchronization process are experimentally verified and compared with the interpolated DFT algorithm.

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“…This influences the reduction of spectral leakage [14]. Ferrero et al [15] and Duda [16] have proposed the windowed interpolation FFT (WIFFT) algorithm in this regards. Nonetheless, the resolution is a major issue in the DFT class of estimators.…”

Section: Introductionmentioning

confidence: 99%

Accurate Real-Time Estimation of Power System Transients Using Constrained Symmetric Strong Tracking Square-Root Cubature Kalman Filter

2019

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The paper presents a fast and accurate algorithm for estimating four significant parameters (i.e., amplitude, frequency, phase angle, and damping factor) of a typical transient signal. The method can be connoted as the constrained symmetric strong tracking square-root cubature Kalman filter (CSSTSCKF). The important aspects of the proposed algorithm are: 1) constraints are imposed on the state vectors by way of a logarithmic barrier function that is either ignored or handled heuristically; 2) symmetric sub-optimal multiple fading factors (FFs) are augmented into the predicted covariance matrix to capture sudden changes and to tune the gain matrix in real-time; moreover, symmetry of the covariance matrix is guaranteed by the influence of Cholesky triangular decomposition; 3) effect of noise can be adjusted by tuning the soften factor. Several case studies have been simulated to evaluate the proposed algorithm with respect to some of the well-known state-of-the-art methods. The real-time performance has been evaluated by flashing the filter codes into an ARM Cortex-M7 processor board and tracking the real-time signal from the experimental test bench. The results, presented herein, indicate that the CSSTSCKF remarkably outperforms all other considered techniques. Furthermore, the stability analysis of the nonlinear filter has been proved based on the constructor expression considering the boundedness of the estimation errors and other sub-items. INDEX TERMS Cholesky triangular decomposition, fading factor (FF), inequality constraints, logarithmic barrier function, power system transient, strong tracking square-root cubature Kalman filter (STSCKF).

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Interpolation Algorithms of DFT for Parameters Estimation of Sinusoidal and Damped Sinusoidal Signals

Cited by 15 publications

References 21 publications

Algorithm for Simultaneous Parameter Estimation of A Multiharmonic Signal

Algorithm for Simultaneous Parameter Estimation of A Multiharmonic Signal

Synchronization of Sampling-Based Measuring Systesm

Accurate Real-Time Estimation of Power System Transients Using Constrained Symmetric Strong Tracking Square-Root Cubature Kalman Filter

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