Amplitude Estimation Algorithm Research Articles

Amplitude estimation of rectangular narrow-band radio pulse with unknown duration and initial phase

This study investigates algorithms for the estimation of amplitude of the radio signal with rectangular envelope and unknown duration and initial phase. The synthesis and analysis of quasi-likelihood and quasi-coherent estimation algorithm have been performed. This algorithm implies that the unknown duration and initial phase are replaced with certain expected values of these parameters. The loss in accuracy of amplitude estimation owing to the a priori lack of knowledge of the duration and the initial phase is analyzed. The quasi-likelihood noncoherent algorithm for amplitude estimation with the initial phase adaptation is synthesized and its statistical characteristics such as the estimate bias and variance are determined. The relationships of the loss in estimation accuracy owing to the a priori lack of knowledge of signal duration are derived. The maximum likelihood algorithm for amplitude estimation was synthesized and analyzed. This algorithm implies that the unknown duration and the initial phase are replaced with their maximum likelihood estimates. The gain in accuracy of the maximum likelihood estimate as compared to the quasi-likelihood ones was investigated. It is shown that a priori lack of knowledge of the signal duration does not affect asymptotically the accuracy of maximum likelihood estimate of amplitude at large values of signal-to-noise ratio.

A simple algorithm for amplitude estimation of distorted power system signal

Abstract This paper presents development and implementation of a novel digital signal processing algorithm for on-line estimation of peak value of the fundamental component of a non-sinusoidal power system signal. The algorithm relies on stable band-pass first and second degree digital integrator based rigorous mathematical deduction and recombines itself with zero-crossing avoiding technique. Compared with the well-established technique such as the enhanced phase-locked-loop (EPLL) based system, the proposed algorithm provides higher degree of immunity and insensitivity to harmonics and noise, and faster response. Based on simulation studies, performances of the proposed algorithm at different operating conditions have been presented and its accuracy and response time have been compared with the EPLL systems. Moreover, a simple laboratory setup implemented by MATLAB and dedicated hardware is built to verify the performance of the proposed algorithm in real time applications. The framework of laboratory prototype has been given out and the necessary modification in proposed algorithm for on-line implementation has been discussed.

Online Monitoring System Design for Roll Eccentricity in Rolling Mills

This paper deals with the parameter estimation and online monitoring of roll eccentricity in rolling mills. Roll-eccentricity-induced disturbances can result in strip thickness deviation and product quality degradation, and a conventional control strategy cannot regulate this kind of periodic disturbances due to its complex characteristics. For the purpose of product quality assessment and monitoring, a performance indicator based on product expectations or the empirical value of quality-related process variables, which can be quantitatively visualized with four zones, is proposed in the high level. In the low level, the key parameters of roll eccentricity are estimated in real time using an adaptive observer for frequency estimation and an adaptive algorithm for amplitude and phase estimation. The performance and effectiveness of the proposed eccentricity monitoring system are demonstrated through a case study of a cold rolling mill from industrial fields.

Parameter estimation under non-stationary circumstances using extended signal model

Abstract. In the context of transient processes in power system measurements, a sampled signal is analyzed with respect to electro-magnetic influences. These are most likely superposed sinusoids that can be found next to the fundamental system sinusoid. However, such signal is not stationary, i.e. has a varying model order which means that temporary and exponentially damped sinusoids appear eventually. In our previous work, the exponential damping was only considered indirectly but not explicitly incorporated in the signal model used. Regarding the amplitude estimation, this led to inaccuracies since the amplitude was incorrectly assumed constant within a window of samples. In this paper, we use ESPRIT's ability to also estimate a parameter of exponential damping, improve the corresponding signal model, advance the amplitude estimation algorithm and back projection algorithm. Especially short-term signal components can be tracked far more precise.

Sparse subband fusion imaging based on parameter estimation of geometrical theory of diffraction model

This study focuses on sparse subband fusion imaging. A method based on high-precision parameter estimation of geometrical theory of diffraction (GTD) model is given. Considering the incoherence problem in each subband data, a coherent processing method is adopted in the paper. Based on an all-pole model, it makes use of the phase difference of pole and scattering coefficient between each sub-band to effectively estimate the incoherent components. After coherent processing, the high and low frequency subband data can be expressed as a uniform all-pole model. The gapped-data amplitude and phase estimation algorithm is adopted to fill up the gapped band. Finally, fusion data is gained by high precision parameter estimation of GTD-all-pole model with full-band data, such as scattering center number, scattering center type and amplitude. The experimental results of simulated data with fixed-points indicate that the resolution of one-dimensional (1D) range profile and 2D inverse synthetic aperture radar (ISAR) image based on this method is better than that of each sub-band. In this way, the validity of the proposed method is proved.

Multi-band Fusion Imaging Based on High Precision Parameter Estimation of Geometrical Theory of Diffraction Model

This paper focuses on multi-band fusion imaging.A method based on high-precision parameter estimation of Geometrical Theory of Diffraction(GTD) model is given.It makes use of the phase difference of pole and scattering coefficient between the all-pole model of each sub-band to estimate the incoherent components.The gapped-data amplitude and phase estimation algorithm is adopted to fill up the gapped band.Finally,fusion data is gained by high precision parameter estimation of geometrical theory of diffraction-all-pole model with full-band data.The simulation indicates that the resolution of 1D range profile and 2D ISAR image based on this method is better than that of sub-band.In this way,the effectiveness of the method is verified.

Simple, fast and accurate eight points amplitude estimation method of sinusoidal signals for DSP based instrumentation

A simple, fast and accurate amplitude estimation algorithm of sinusoidal signals for DSP based instrumentation is proposed. It is shown that eight samples, used in two steps, are sufficient. A practical analytical formula for amplitude estimation is obtained. Numerical results are presented. Simulations have been performed when the sampled signal is affected by white Gaussian noise and when the samples are quantized on a given number of bits.

Optimal Gain Filter Design for Perceptual Acoustic Echo Suppressor

This Letter proposes an optimal gain filter for the perceptual acoustic echo suppressor. We designed an optimally-modified log-spectral amplitude estimation algorithm for the gain filter in order to achieve robust suppression of echo and noise. A new parameter including information about interferences (echo and noise) of single-talk duration is statistically analyzed, and then the speech absence probability and the a posteriori SNR are judiciously estimated to determine the optimal solution. The experiments show that the proposed gain filter attains a significantly improved reduction of echo and noise with less speech distortion.

A New Power System Digital Harmonic Analyzer

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, new digital instruments measuring power-quality indicators and harmonic analyzers are developed. A new technique for simultaneous local system frequency and amplitudes of the fundamental and higher harmonics estimation from either a voltage or current signal is presented. The structure consists of three decoupled modules: the first one for an adaptive filter of input signal, the second one for frequency estimation, and the third one for harmonic amplitude estimation. A very suitable algorithm for frequency and harmonic amplitude estimation is obtained. This technique provides accurate frequency estimates with error in the range of 0.002 Hz and amplitude estimates with error in the range of 0.03% for SNR <formula formulatype="inline"><tex>$=$</tex> </formula> 60 dB in about 25 ms. The theoretical basis and practical implementation of the technique are described. To demonstrate the performance of the developed algorithm, computer simulated data records are processed. Data of the distribution power system voltage signals are also collected in the laboratory environment and are processed in a newly developed digital PC-based harmonic analyzer. It has been found that the proposed method really meets the need of offline applications. Even more, by using the parallel computation algorithms, this method should meet the need of online applications and should be more practical. </para>

The Pathwise Semi-Blind Algorithm for Downlink DS-CDMA Systems Using Antenna Arrays

This paper presents a semi-blind algorithm for multiuser interference cancellation and fading amplitude estimation for downlink MIMO DS-CDMA systems with multipath fading channels. Taking advantage of the space-time information of the parametric multipath channel, the proposed algorithm first uses a space-time channel decoupler to suppress multiuser interference and then decomposes the channel into a set of parallel subchannels each containing the signal of the desired user on an individual multipath. Two criteria, the complementary orthogonal projection (COP) and the minimum variance distortionless response (MVDR), are employed by the space-time decoupler to achieve interference suppression and signal separation. The fading amplitudes can then be estimated from the eigen space of the output of the space-time channel decoupler. It follows that the signal of interest can be maximally combined in a pathwise manner and then differentially decoded.

Fast algorithms for frequency, amplitude and phase evaluation of nonsinusoidal signals with noises

A fast and accurate algorithm for frequency, amplitude and phase estimation of the signals with white Gaussian noises is proposed in this paper. The proposed algorithm need two sample and computation process, one of which is used for frequency estimation in half cycle of the signal and another of which is used for amplitude and phase estimation in another half cycle. The proposed algorithm spends at most 1 cycle. Frequency estimation is based on numerical differentiation, and amplitude and phase estimation is based on fast Fourier Transform. With an initial sample frequency of 512 × 50 Hz, the signal is sampled and the frequency of the signal with white Gaussian noises is estimated at an error of 0.001% over a range of 1 Hz–1000 kHz. With another sample frequency based on the estimated frequency, the signal is once again sampled and the amplitude of the signal is estimated an error of 0.001% over a range of 1 V–320 V and the phase angle of the signal is estimated an accuracy of 0.001% over a range of 0–360. Using Matlab software, the simulation results of the test example are satisfactory.

Adaptive beamforming for quadrupole resonance

We present several adaptive beamforming approaches to improve the quadrupole resonance (QR) signal detection performance via exploiting both the spatial and temporal correlation of radio frequency interferences (RFIs). We operate in the framework of signal amplitude estimation with known signal waveform and make use of three adaptive beamforming approaches, viz., the standard Capon beamformer (SCB), the robust Capon beamformer (RCB), and the amplitude and phase estimation (APES) algorithm, to develop several new approaches for mitigating the spatially and temporally correlated RFIs. Simulated and experimental results are provided to demonstrate the effectiveness of the proposed approaches.

Nonparametric spectral analysis of gapped data via an adaptive filtering approach

We present an algorithm for nonparametric complex spectral analysis of gapped data via an adaptive finite impulse response (FIR) filtering approach, referred to as the gapped-data amplitude and phase estimation (GAPES) algorithm. The incomplete data sequence may contain gaps of various sizes. The GAPES algorithm iterates the following two steps: (1) estimating the adaptive FIR filter and the corresponding complex spectrum via amplitude and phase estimation (APES), a nonparametric adaptive FIR filtering approach, and (2) filling in the gaps via a least-squares APES fitting criterion. The initial condition for the iteration is obtained from the available data segments via APES. Numerical results are presented to demonstrate the effectiveness of the proposed GAPES algorithm.

Nonlinear RLS algorithm for amplitude estimation in class A noise

An adaptive nonlinear recursive least square (RLS) algorithm for amplitude estimation in class A noise is presented. For Gaussian input signal and class A noise, its mean and mean-square behaviours are studied. It is shown that the linear RLS and nonlinear RLS algorithm with the clipper function are stable in the mean and mean square. For non-Gaussian input, amplitude estimation in CDMA communication is presented. Simulation results show that the nonlinear RLS can provide good performance close to the Cramer–Rao bound and outperform the nonlinear LMS and the conventional RLS in impulse noise.

Using APES for interferometric SAR imaging

We present an adaptive finite impulse response (FIR) filtering approach, which is referred to as the Amplitude and Phase EStimation (APES) algorithm, for interferometric synthetic aperture radar (SAR) imaging. We compare the APES algorithm with other FIR filtering approaches including the Capon and fast Fourier transform (FFT) methods. We show via both numerical and experimental examples that the adaptive FIR filtering approaches such as Capon and APES can yield more accurate spectral estimates with much lower sidelobes and narrower spectral peaks than the FFT method. We show that although the APES algorithm yields somewhat wider spectral peaks than the Capon method, the former gives more accurate overall spectral estimates and SAR images than the latter and the FFT method.