Frequency Estimation Method Research Articles

Comparison of sine-wave frequency estimation methods in respect of speed and accuracy for a few observed cycles distorted by noise and harmonics

Comparison of sine-wave frequency estimation methods in respect of speed and accuracy for a few observed cycles distorted by noise and harmonics

Long Horizon Repeated Games: How Does Ending Rule Affect Decisions in High Games

This paper looks to see if subjects approach long, indefinitely repeated Prisoner's Dilemma games featuring discounted payoffs with an option to opt out differently from how they approach long, indefinitely repeated Prisoner's Dilemma games that are randomly terminated. I show under relatively general assumptions that the critical δ ∗ -value, above which cooperation can be supported as a Subgame Perfect Equilibrium, differs between the two environments. A between-subject design with δ = 0.98 was used to determine if subject behavior did vary by treatment. First period and all period cooperation rates were found to be higher in the random termination treatment compared to the discounted treatment. The evolution of cooperation across supergames also differed between the two treatments. Behavior in the discounted treatment did not follow the patterns typically observed in the literature. Lastly, the Strategy Frequency Estimation Method (SFEM) was used to determine whether or not subjects in different treatments used different repeated game strategies. I find that subjects in the discounted treatment were more likely to play strategies that defect initially (All D, STFT), but cooperative subjects tended to play more forgiving strategies (TFT, STFT). Conversely, subjects in the randomly terminated treatment tended to play more initially cooperative, yet less forgiving strategies (Grim, Grim2).

Maximum Likelihood Parameter Estimation of Unbalanced Three-Phase Power Signals

Accurate detection of the system parameters in unbalanced three-phase power systems is a prerequisite for the optimal operation and control of future smart grids. However, theoretical and practical performance bounds of various estimators for unbalanced systems are only just being established. To this end, we introduce the appropriate Cramer–Rao lower bounds (CRLBs) for frequency estimation, based on the $\alpha \beta$ -transformed unbalanced voltage contaminated with noise. Next, for rigor, the maximum likelihood estimation (MLE) method for frequency estimation is introduced as a maximizer of an “augmented periodogram.” The underlying augmented complex statistics is shown to cater for all the available second-order information, including the noncircularity associated with unbalanced systems. To find the ML solution, Newton’s iterative method is employed and its initialization is implemented by a discrete Fourier transform-based dichotomous search technique. We show that the MLE of phases and amplitudes of both the positive and negative phase-sequence components within the $\alpha \beta$ -transformed voltage can be generically derived based on the ML frequency estimates. In this way, a unified framework is provided to accurately detect voltage characteristics of the positive and negative phase-sequence components within an unbalanced three-phase power system when its frequency experiences off-nominal conditions. Simulations verify that the proposed MLE approaches theoretical CRLBs for all parameters under consideration.

Joint frequency offset, time offset, and channel estimation for OFDM/OQAM systems

Among the multicarrier modulation techniques considered as an alternative to orthogonal frequency division multiplexing (OFDM) for future wireless networks, a derivative of OFDM based on offset quadrature amplitude modulation (OFDM/OQAM) has received considerable attention. In this paper, we propose an improved joint estimation method for carrier frequency offset, sampling time offset, and channel impulse response, needed for the practical application of OFDM/OQAM. The proposed joint ML estimator instruments a pilot-based maximum-likelihood (ML) estimation of the unknown parameters, as derived under the assumptions of Gaussian noise and independent input symbols. The ML estimator formulation relies on the splitting of each received pilot symbol into contributions from surrounding pilot symbols, non-pilot symbols and additive noise. Within the ML framework, the Cramer-Rao bound on the covariance matrix of unbiased estimators of the joint parameter vector under consideration is derived as a performance benchmark. The proposed method is compared with a highly cited previous work. The improvements in the results point to the superiority of the proposed method, which also performs close to the Cramer-Rao bound.

A Novel Residual Frequency Estimation Method for GNSS Receivers.

In Global Navigation Satellite System (GNSS) receivers, residual frequency estimation methods are traditionally applied in the synchronization block to reduce the transient time from acquisition to tracking, or they are used within the frequency estimator to improve its accuracy in open-loop architectures. There are several disadvantages in the current estimation methods, including sensitivity to noise and wide search space size. This paper proposes a new residual frequency estimation method depending on differential processing. Although the complexity of the proposed method is higher than the one of traditional methods, it can lead to more accurate estimates, without increasing the size of the search space.

Application of a Hybrid Method for Power System Frequency Estimation with a 0.2-second Sampled Period

The signal processing technique is one of the principal tools for diagnosing power quality (PQ) issues in electrical power systems. The Discrete Fourier Transform (DFT) is a frequency analysis technique used to process power system signals and identify PQ problems. However, the DFT algorithm may lead to spectral leakage and picket-fence effect problems for asynchronously sampled signals that contain harmonic, inter-harmonic, and flicker components. To resolve this shortcoming, a hybrid method for frequency estimation based on a second-level DFT approach and a frequency-domain interpolation algorithm to obtain the accurate fundamental frequency of a power system is proposed in this paper. This method uses a second-level DFT to compute the cosine and sine parts for the fundamental frequency components of the acquired signals. Then, a frequency-domain interpolation approach is adopted to determine the amplitude ratio for the cosine and sine parts of the system’s fundamental frequency. A set of mixed signals with harmonic, inter-harmonic, and flicker components with the fundamental frequency deviation is used. The evaluation results demonstrate the superiority of the new method over other approaches for assessing asynchronously sampled signals contaminated with noise, harmonic, inter-harmonic, and flicker components.

An Improved Time‐Frequency Analysis Method for Instantaneous Frequency Estimation of Rolling Bearing

Instantaneous frequency estimation of rolling bearing is a key step in order tracking without tachometers, and time‐frequency analysis method is an effective solution. In this paper, a new method applying the variational mode decomposition (VMD) in association with the synchroextracting transform (SET), named VMD‐SET, is proposed as an improved time‐frequency analysis method for instantaneous frequency estimation of rolling bearing. The SET is a new time‐frequency analysis method which belongs to a postprocessing procedure of the short‐time Fourier transform (STFT) and has excellent performance in energy concentration. Considering nonstationary broadband fault vibration signals of rolling bearing under variable speed conditions, the time‐frequency characteristics cannot be obtained accurately by SET alone. Thus, VMD‐SET method is proposed. Firstly, the signal is decomposed into several intrinsic mode functions (IMFs) with different center frequency by VMD. Then, effective IMFs are selected by mutual information and kurtosis criteria and are reconstructed. Next, the SET method is applied to the reconstructed signal to generate the time‐frequency representation with high resolution. Finally, instantaneous frequency trajectory can be accurately extracted by peak search from the time‐frequency representation. The proposed method is free from time‐varying sidebands and is robust to noise interference. It is proved by numerical simulated signal analysis and is further validated by lab experimental rolling bearing vibration signal analysis. The results show this method can estimate the instantaneous frequency with high precision without noise interference.

ESPRIT for Multidimensional General Grids

We present a method for complex frequency estimation in several variables, extending the classical one-dimensional ESPRIT algorithm, and consider how to work with data sampled on nonstandard domains, i.e., going beyond multirectangles.

Fast Frequency Estimation With Prior Information

A fast gridless method for sparse frequency estimation in the presence of prior information is presented. It allows arbitrarily sampled data and has a significantly smaller complexity than the existing gridless sparse recovery methods. The proposed method achieves good frequency estimation accuracy and resolution performance in numerical simulations. It is also useful where no prior knowledge is available.

Hydrodynamic analysis of floating structures with baffled ARTs

In ocean industry, free surface type ART (Anti Roll tank) system has been widely used to suppress the roll motion of floating structures. In those, various obstacles have been devised to obtain the sufficient damping and to enhance the controllability of freely rushing water inside the tank. Most of previous researches have paid on the development of simple mathematical formula for coupled ship-ARTs analysis although other numerical and experimental approaches exist. Little attention has been focused on the use of 3D panel method for preliminary design of free surface type ART despite its advantages in computational time and general capacity for hydrodynamic damping estimation. This study aims at developing a potential theory based hydrodynamic code for the analysis of floating structure with baffled ARTs. The sloshing in baffled tanks is modeled through the linear potential theory with FE discretization and it coupled with hydrodynamic equations of floating structures discretized by BEM and FEM, resulting in direct coupled FE-BE formulation. The general capacity of proposed formulation is emphasized through the coupled hydrodynamic analysis of floating structure and sloshing inside baffled ARTs. In addition, the numerical methods for natural sloshing frequency tuning and estimation of hydrodynamic damping ratio of liquid sloshing in baffled tanks undergoing wave exiting loads are developed through the proposed formulation. In numerical examples, effects of natural frequency tuning and baffle ratios on the maximum and significant roll motions are investigated.

Amplitude and Frequency Estimation of Exponentially Decaying Sinusoids

An online method for amplitude and frequency estimation of exponentially decaying sinusoids is proposed with a moving-window discrete Fourier transform (MWDFT) filter and frequency-locked loop. The tuned filter characteristics of MWDFT is modified into more flat characteristic around the center frequency with negative feedback, which increases the bandwidth of the filter. An adaptive sampling pulse adjustment mechanism is incorporated in the proposed structure for online estimation of frequency. Hence, the frequency error was exploited to achieve synchronization between in-phase component of MWDFT and input signal of estimation. The amplitude is estimated in online from the in-phase and quadrature-phase components of MWDFT. The performance of the proposed method is compared with the existing techniques and experimentally validated on single-link flexible manipulator system for the online estimation of frequency and amplitude of tip deflection signal. The experimental investigation prove that the proposed online technique performs well over the existing techniques.

A novel center of mass method for estimation of center frequency and spectral edges in CR using filter banks

In this paper, we propose a novel multistage DFT based polyphase filter bank technique using center of mass approach for estimating center frequency, detecting spectral edges and identifying spectral holes in wideband cognitive radio (CR) for efficient utilization of radio frequency spectrum. Spectral holes are identified by measuring energy at the output of individual subband of filter banks. Accuracy of spectral holes detection depends on frequency resolution of subbands and can be increased with an increase in number of DFT points, however, at the expense of computational complexity. In order to reduce complexity our algorithm starts with a coarser spectral resolution in the first stage. If a primary user appears over more than one subband, center frequency can be estimated in the first stage using proposed approach. However, if the primary user appears exclusively within a single subband, center frequency can be estimated at the second stage. For center frequency estimation, we propose a novel center of mass approach to achieve better precision, where mass is related to energy and distance is related to frequency. Exhaustive simulation results show that center frequency estimation using proposed multistage polyphase filter bank based on center of mass reduces computational complexity and has higher precision compared to conventional filter bank methods.

Instantaneous Frequency Estimation for Nonlinear FM Signal Based on Modified Polynomial Chirplet Transform

Time-frequency analysis (TFA) is an effective tool to identify the signal frequency components and to reveal their time variant features. In this paper, a new instantaneous frequency (IF) estimation method is proposed for signals with heavy noise, which is based on a polynomial chirplet transform and a ridge curve extraction scheme. Based on this method, an iterative stepwise refinement algorithm is developed to generate a time-frequency distribution (TFD) with satisfactory energy concentration. Both simulated signals and experimental vibration signals are used to validate the performance of the proposed methods. The results demonstrate that the proposed TFA method is more effective in processing the nonstationary signals with heavy noise. Further, it can perform an accurate evaluation of the IF and obtain a clear TFD.

A context-aware frequency estimation method for wireless passive resonant SAW sensors

PurposeThis paper aims to present an context evaluation and frequency measurement method for surface acoustic wave (SAW) resonant sensor.Design/methodology/approachThis method is based on a signal subspace construction, which, along with assembling optional value set, provides the results.FindingsThe method can assess the application context and improve the resolution and accuracy of the passive wireless SAW resonator sensor system.Originality/valuePassive wireless SAW resonators have been used as sensor elements for different physical parameters such as temperature, pressure and force in a number of industrial and medical applications. Various wireless channel environments introduce different application contexts.

Laser-Interferometric Broadband Seismometer for Epicenter Location Estimation.

In this paper, we suggest a seismic signal measurement system that uses a laser interferometer. The heterodyne laser interferometer is used as a seismometer due to its high accuracy and robustness. Seismic data measured by the laser interferometer is used to analyze crucial earthquake characteristics. To measure P-S time more precisely, the short time Fourier transform and instantaneous frequency estimation methods are applied to the intensity signal () of the laser interferometer. To estimate the epicenter location, the range difference of arrival algorithm is applied with the P-S time result. The linear matrix equation of the epicenter localization can be derived using P-S time data obtained from more than three observatories. We prove the performance of the proposed algorithm through simulation and experimental results.

New statistical methods for estimation of recombination fractions in F2 population

BackgroundDominant markers in an F2 population or a hybrid population have much less linkage information in repulsion phase than in coupling phase. Linkage analysis produces two separate complementary marker linkage maps that have little use in disease association analysis and breeding. There is a need to develop efficient statistical methods and computational algorithms to construct or merge a complete linkage dominant marker maps. The key for doing so is to efficiently estimate recombination fractions between dominant markers in repulsion phases.ResultWe proposed an expectation least square (ELS) algorithm and binomial analysis of three-point gametes (BAT) for estimating gamete frequencies from F2 dominant and codominant marker data, respectively. The results obtained from simulated and real genotype datasets showed that the ELS algorithm was able to accurately estimate frequencies of gametes and outperformed the EM algorithm in estimating recombination fractions between dominant loci and recovering true linkage maps of 6 dominant loci in coupling and unknown linkage phases. Our BAT method also had smaller variances in estimation of two-point recombination fractions than the EM algorithm.ConclusionELS is a powerful method for accurate estimation of gamete frequencies in dominant three-locus system in an F2 population and BAT is a computationally efficient and fast method for estimating frequencies of three-point codominant gametes.

High-precision frequency estimation for frequency modulated continuous wave laser ranging using the multiple signal classification method.

The long fiber frequency sampling method is used to eliminate the nonlinearity of laser tuning in the frequency-modulated continuous-wave laser detection and ranging (FMCW ladar) technique. However, although it has high precision, it is affected by the picket fence effect and spectrum leakage. In this paper, we propose a novel frequency estimation method, multiple signal classification (MUSIC), to be used instead of the conventional fast Fourier transform (FFT)-based algorithm in order to obtain better range precision. The proposed method was verified by experiments. In the experiments, when the distance was up to 3.814m and chirped bandwidth was equal to 20nm (2.5THz), the full width at half-maximum of the range peak, which represented the estimated precision of frequency obtained by MUSIC, was 20μm, and it was improved by 7 times compared to the FFT-based method. Meanwhile, to evaluate the performance of the proposed method, the frequency estimation according to the Cramer-Rao lower bound (CRLB) was also performed. The experimental results have shown that the mean square error of distance estimation based on the MUSIC algorithm is 0.56μm, which is much closer to the CRLB of 0.18μm than the mean square error of the conventional FFT-based method. Furthermore, we demonstrated that the MUSIC estimator has an unparalleled advantage over other estimators in the high-precision ranging fields.

2D DOA and Frequency Estimation Method with One Vector-Sensor and Two Pressure Sensors Based on ESPRIT and Signal Power

We use one vector and two pressure sensors to form a sparse large aperture L-shape array for high performance two-dimensional (2D) direction of arrival (DOA) and frequency estimation. Because the number of sensors is small and there is only one vector sensor in the presented array, thus, the installation of sensors in the array is simpler and installation error is smaller, than the conventional array. Meanwhile, a high performance 2D DOA and frequency estimation method is presented. Firstly, utilizing single vector sensor and based on the ESPRIT, a group coarse 2D DOA and frequency parameters are obtained. Secondly, to restrain space noise or interference, a matrix filter is utilized to process the covariance matrix which comes from sensor array, so as to form a new covariance matrix which possesses high signal to noise ratio. Thirdly, utilizing the new covariance matrix and based on the ESPRIT again, accurate but ambiguity angles estimates are obtained. Fourthly, one signal power estimator and one optimization method are presented to solve the angle ambiguity and frequency ambiguity problems, respectively. The proposed method gains a high performance 2D DOA and frequency estimation results. Numerical simulations are performed to verify the feasibility of the proposed method.

Improved Frequency Estimation in Unbalanced Three-Phase Power System Using Coupled Orthogonal Constant Modulus Algorithm

A new iterative method for frequency estimation in the unbalanced three-phase power system is proposed. The proposed solution is based on the transformation of unbalanced three-phase voltage signal into a complex exponential by using the orthogonal constant modulus algorithm. In addition, based on the transformed signal, a simple adaptive algorithm for frequency estimation is proposed. Beside the proposed approach, any frequency estimator designed for a single-tone complex exponential can be used here, which is also the advantage of the proposed method. Simulation results confirm that the proposed algorithm exhibits better performance compared to the considered algorithms.

High-Accuracy Frequency Analysis of Harmonic Signals Using Improved Phase Difference Estimation and Window Switching

Accurate frequency tracking of harmonic signals is an essential process for analysis of musical instrument and singing sounds. For fine frequency estimation, we propose two methods for enhancement of the phase difference estimation (PDE). The first method is improved PDE that maximises the signal level at the frequency estimation position, which is effective especially at low signal-to-noise ratio (SNR). The second method is window switching that minimises the effects of harmonics by suppressing their sidelobe levels, which is effective at high SNR. Window switching is also applicable to existing fine frequency estimation methods as well as the PDE and improved PDE. Experimental results and application examples show that the proposed methods show meaningful improvements over the PDE and are effective for high-accuracy frequency analysis. The proposed methods can be adopted as a module for sound analysis and processing tools and software, which are expected to contribute to the comprehensive analysis of musical signals.