Frequency Sampling Method Research Articles

Investigation of damping coefficients for elastic collision particles utilizing the acoustic frequency sampling method

The damping coefficient serves to quantify the energy dissipation in particle collisions and constitutes a crucial parameter in discrete element simulations. Nevertheless, the factors influencing the damping coefficient remain unclear, and the damping coefficients of the majority of materials have not been precisely determined. In this investigation, the damping coefficients of eight representative particles were studied using the acoustic frequency sampling method, and the correlations between these coefficients and collision velocity, material density, and elastic modulus were analyzed. The findings indicate that damping coefficients exhibit insensitivity to velocity in strongly elastic and moderately elastic material particles. Conversely, for weakly elastic material particles, damping coefficients demonstrate an increase with rising velocity. The damping coefficient of metallic particles exhibits a linear relationship with material density and elastic modulus.

Restitution coefficient of various particles based on acoustic technology

The restitution coefficient is used to characterize the energy loss in particle impact, which is an important parameter for discrete element simulation and mechanical system motion analysis. However, the restitution coefficient of many materials needs to be determined, and the key material properties affecting the restitution coefficient are still unclear. In this paper, the acoustic frequency sampling method was used to study the restitution coefficients of 10 representative particles. The effects of material density and specific strength on the restitution coefficient and the relationship between the restitution coefficient and the damping coefficient were investigated. The results show that the particle restitution coefficient is inversely proportional to the density except for aluminium. The relationship between particle restitution coefficient and specific strength is not significant.

КОЛЕБАНИЯ ЗАЩЕМЛЕННОЙ ПРЯМОУГОЛЬНОЙ ПЛАСТИНЫ ПРИ РАСТЯЖЕНИИ – СЖАТИИ ЕЕ ПЛОСКОСТИ

The dependence of the natural oscillation frequency of a pinched rectangular plate on the magnitude of uniformly distributed compressive (or tensile) forces applied to all its faces is investigated. The problem is solved using two hyperbolo-trigonometric series satisfying all the conditions of the boundary value problem. A resolving infinite homogeneous system of linear algebraic equations is obtained with respect to a single sequence of coefficients of a series, which contains the natural frequency and intensity of the longitudinal load as parameters. The natural frequency was calculated for a number of values of the longitudinal load up to its critical value. At the same time, an iterative method of finding nontrivial solutions of the system was used in combination with the frequency sampling method (the “shooting” method). It is established that with increasing compressive load, the natural frequency of the square plate decreases according to the parabolic law. Numerical results are compared with the results of other authors.

Temperature influence on optical fiber and temperature compensation method for a frequency modulation continuous wave absolute distance measurement system.

A temperature compensation method is proposed to solve the ranging precision decrease problem of the frequency-modulated continuous wave distance measurement system. The set of phases spread frequency sampling method is used to correct the beat frequency signal non-linearity. The influence model of temperature on the optical fiber auxiliary interferometer is studied. The experimental results show that distance measurement error decreases from 0.3432 mm to 0.02260 mm, and the mean measurement standard deviation decreases from 0.1088 mm to 0.01733 mm on a maximum measurement range of 1.6 m after compensation.

Fast and Accurate Brillouin Optical Time-Domain Sensing by Sparse Frequency Sampling and ANN-Based Recover Method

We propose a novel sparse frequency sampling and Brillouin scattering spectrum (BSS) recover method to greatly reduce the acquisition time of the frequency-sweep based Brillouin optical time domain sensor (BOTDS) without increasing hardware complexity. In the proposed method, the acquired BSSs only contain a few frequency points and thus show low resolution due to the sparse frequency sampling strategy. Then an artificial neural network (ANN) is used to accurately recover the BSSs with sparse frequency sampling to that with normal frequency sampling, and thus achieve fast and accurate temperature/strain measurement. In a proof-of-concept experiment, we measured the BSS of a 3 km sensing fiber and achieved 3 m spatial resolution by using a Brillouin optical time domain reflectometry (BOTDR) sensor. Through sparse frequency sampling, the data acquisition time is 5.5% with respect to that of the normal sampling. When the average (AVG) times of BSS is higher than 1000, the temperature measurement uncertainty is 0.2 °C.

Laser frequency scanning interference nonlinear correction method based on Lomb-Scargle algorithm

Laser frequency scanning interference technology has become a research hotspot due to its high precision and strong anti-interference capability and other advantages. The nonlinear problem of laser frequency modulation has always been a key factor affecting the accuracy of the measurement system. The most direct result of the nonlinearity of frequency modulation is that the spectrum of the beat signal is severely broadened, resulting in a decrease in the ranging accuracy. In order to solve this problem, this paper proposes a nonlinear correction method based on the Lomb-Scargle algorithm, and builds a laser frequency sweep interferometry system with an auxiliary interferometer. The phase is extracted by performing Hilbert transform on the auxiliary path beat signal, thereby generating a new time series based on the extracted phase information. The generated time series carries the phase change information of the auxiliary path beat signal, and it is combined with the Lomb-Scargle algorithm to perform the nonlinear correction of the measurement system and the frequency calculation of the beat signal simultaneously. As a verification, the targets in the range of 0.5–1.3 m are measured with a maximum error of 14 μm. The traditional frequency sampling method is limited by the Nyquist sampling theorem, and the laser emission and reception need to travel a round-trip distance, which means that the frequency sampling method must meet the requirement that the distance of the measured target cannot exceed a quarter of the optical path difference of the auxiliary interferometer. Therefore, the range of distance measurement is limited when the optical path difference of the auxiliary interferometer is constant. Different from the correction principle of the traditional frequency sampling method, the correction method proposed in this paper does not use the beat signal of the auxiliary path to resample the measurement path, so there is no need to satisfy the condition that the optical path difference of the auxiliary interferometer is greater than four times the measuring distance. Therefore, in the case of a certain optical path difference of the auxiliary interferometer, it can provide a way to increase the ranging range of the system.

Theoretical Analysis and Design Optimization for Multi-GNSS Direct Radio Frequency Sampling Receiver

Abstract: Recently, a considerable amount of research has been conducted on multiple GNSS receivers using the Direct RF sampling concept. This approach greatly reduces the hardware requirements of the traditional receiver by placing the analog-todigital converter as close as possible to the antenna, eliminating the mixer stages. Furthermore, directly sampling the RF signal using the ADC allows for a more efficient design. In this paper, a Multi-GNSS Direct Radio Frequency Sampling Method is designed, optimized, and its performance is presented for several GNSS signals, including GPS L1, GPS L2, and GPS L5. The implemented method is used to find the ranges of valid sampling frequencies in single and multiple band RF signal cases. The algorithm presented results in an easier way to find valid sampling frequencies and a straightforward implementation without the need for complicated mathematical calculations. We consider aliasing issues and computational problems, providing a full theoretical and practical analysis compared to previously presented algorithms in the literature. This paper also examines the relationship between the sampling frequency, noise folding, and its effect on the signal-to-noise ratio (SNR), thus allowing for the selection of the optimal sampling frequency.

Ecology and “bird-habitat” relationship in the cedar forest of Aurès mountain (Eastern Algeria)

Abstract This work aims to compile the birds breeding in the cedar forest of Aurès and to study the “Bird – Habitat” relationships. The data was collected using the progressive frequency sampling method that served as the basis for the diagnosis build on an analytical approach designed around three tools (mutual information, ecological profiles, modelling). Information theory tools allowed us to identify the indicator values of species as well as the most important descriptors. Habitat modelling has been prepared for species with a high indicator value. The logistic models are shown to be well adapted to the nature of the ornithological data. They related the occurrences of the species with the dendro-ecological descriptors. The 70 surveys carried out enabled us to identify 32 bird species. The ecological analysis revealed the most active descriptors and the species with high indicator value. The best-fitting models are those of Short-toed Treecreeper with positive effect of dead wood, density of trees and variability of distances between trees, and European Robin with negative effect of anthropization and general coverage, and positive effect of crown parametres. We conclude that promoting forest structural complexity by diversifying management regimes will be key to maintain avian biodiversity in cedar forests.

A Natively Fixed-Point Run-Time Reconfigurable FIR Filter Design Method for FPGA Hardware

We present a natively fixed-point filter design method that targets FPGA-based Reconfigurable Finite Impulse Response (RFIR) filters for Software Defined Radio applications. The Filter Designer is capable of reconfiguring cut-off frequencies on-the-fly at run-time; with other parameters, such as filter length and window type, configurable at compile-time. The ability to compute filter coefficients directly on FPGAs is compelling, as much lower latencies can be achieved when compared to RFIRs programmed with embedded processors. In this work we discuss several filter design techniques from the literature and investigate their suitability for implementation on FPGAs. A hybrid method combining window and frequency sampling methods is developed and implemented on a Xilinx Zynq-7000 SoC. We explore the limitations of designing filters in fixed-point arithmetic and consider the effects filter length and wordlength have on filter quality. Results show that the proposed algorithm generates good-quality filters that display stopband attenuation up to 88dB, transition bandwidths less than 1% of the sample rate, and low resource utilisation. Most notably, we found that our method is up to three orders of magnitude faster than an equivalent software implementation, with execution times as low as 2.52 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> , enabling radio applications in which latency is a principal constraint.

Differentiable Artificial Reverberation

We propose differentiable artificial reverberation (DAR), a family of artificial reverberation (AR) models implemented in a deep learning framework. Combined with the modern deep neural networks (DNNs), the differentiable structure of DAR allows training loss gradients to be back-propagated in an end-to-end manner. Most of the AR models bottleneck training speed when implemented as is in the time domain and executed with a parallel processor like GPU due to their infinite impulse response (IIR) filter components. We tackle this by further developing a recently proposed acceleration technique, which borrows the frequency-sampling method (FSM). With the proposed DAR models, we aim to solve an artificial reverberation parameter (ARP) estimation task in a unified approach. We design an ARP estimation network applicable to both analysis-synthesis (RIR-to-ARP) and blind estimation (reverberant-speech-to-ARP) tasks. And using different DAR models only requires slightly a different decoder configuration. This way, the proposed DAR framework overcomes the previous methods' limitations of task-dependency and AR-model-dependency.

Frequency modulation nonlinear correction and range-extension method based on laser frequency scanning interference.

A phase spread frequency sampling method is proposed. This method can be used to correct the nonlinearity in the beat frequency of a measurement signal. The proposed method expands the phase of the auxiliary interference beat signal, thereby satisfying the Nyquist sampling theorem, correcting the nonlinearity in the beat frequency of the measured signal, and solving the problem of limited range. The conditions over which the frequency sampling method can be applied are expanded. The measurement range is flexibly expanded by performing multiple phase expansions.

Sparsity Promoting Frequency Sampling Method for Estimation of Displacement and Self-Mixing Interferometry Parameters

This paper exploits the difference in amplitude spectrum of perturbed and unperturbed phase of self-mixing (SM) laser, to propose a new method for estimation of coupling factor (C), line-width enhancement factor (LEF), as well as displacement of the vibrating target in three major feedback regimes, i.e, weak-, moderate- and strong-feedback regimes. This result thus fills the gap in limitation of previous methods restricted to fewer regimes. The displacement of target is assumed to be bandlimited and sparse in frequency domain. The proposed algorithm showed an average of 1.0168 nm RMS error in displacement estimation corresponding to single- and multi-tone vibrations of amplitudes varying from 3 to 30 times that of laser's wavelength, with percentage error of 1.15% and 3.31% in C and LEF estimations, from simulated SM laser signals. Using an SM sensor based on a laser diode emitting at 785 nm wavelength, the proposed method has achieved an average RMS error of 21 nm in weak-, moderate- and strong-feedback regimes, corresponding to a vibrating target of 5 micrometer peak-peak amplitude.

Exploring applications of Frozen Newton Method in the design of digital filter

Digital filters are popularly used in digital signal processing. The design of these filters can be done using different methods of which the rectangular window method and Frequency sampling methods are commonly used. Filter design using wavelet coefficients also shows better response. In this paper, we explore the use of the Frozen Newton method in improving the response of the filter designed using these methods. This iterative computing is applied considering the Taylor series expansion of the function up to the first order term called the Jacobian

Instantaneous frequency analysis of broadband LFM signals by photonics-assisted equivalent frequency sampling

We propose a photonics-assisted equivalent frequency sampling (EFS) method to analyze the instantaneous frequency of broadband linearly frequency modulated (LFM) microwave signals. The proposed EFS method is implemented by a photonic scanning receiver, which is operated with a frequency scanning rate slightly different from the repetition rate of the LFM signals. Compared with the broadband LFM signal analysis based on temporal sampling, the proposed method avoids the use of high-speed analog to digital converters, and the instantaneous frequency acquisition realized by frequency-to-time mapping is also simplified since real-time Fourier transformation is not required. Feasibility of the proposed method is verified through an experiment, in which frequency analysis of Kα-band LFM signals with a bandwidth up to 3 GHz is demonstrated with a moderate sampling rate of 100 MSa/s. The proposed method is highly demanded for analyzing the instantaneous frequency of broadband LFM signals used in radar and electronic warfare systems.

An Overview of FIR Filter Design in Future Multicarrier Communication Systems

Future wireless communication systems are facing with many challenges due to their complexity and diversification. Orthogonal frequency division multiplexing (OFDM) in 4G cannot meet the requirements in future scenarios, thus alternative multicarrier modulation (MCM) candidates for future physical layer have been extensively studied in the academic field, for example, filter bank multicarrier (FBMC), generalized frequency division multiplexing (GFDM), universal filtered multicarrier (UFMC), filtered OFDM (F-OFDM), and so forth, wherein the prototype filter design is an essential component based on which the synthesis and analysis filters are derived. This paper presents a comprehensive survey on the recent advances of finite impulse response (FIR) filter design methods in MCM based communication systems. Firstly, the fundamental aspects are examined, including the introduction of existing waveform candidates and the principle of FIR filter design. Then the methods of FIR filter design are summarized in details and we focus on the following three categories—frequency sampling methods, windowing based methods and optimization based methods. Finally, the performances of various FIR design methods are evaluated and quantified by power spectral density (PSD) and bit error rate (BER), and different MCM schemes as well as their potential prototype filters are discussed.

Sparse Nonuniform Frequency Sampling for Fast SFCW Radar Imaging

Stepped frequency continuous wave (SFCW) radar achieves wide bandwidth by synthesizing series of monochromatic pulses in a consecutive manner. Uniform frequency sampling is often performed with a constant frequency step, which in turn limits the maximum unambiguous range achievable by the radar to reliably distinguish targets. Thus, a small frequency step must be selected when clutters exist at long distances even though the target of interests is located at much closer distances. This is costly since a large number of frequencies must be synthesized, which leads to slow acquisition speed. In this paper, a sparse nonuniform frequency sampling method is proposed to effectively reduce the number of frequencies while suppressing aliasing effects from clutters. The Poisson Sum Formula is utilized to derive a deterministic formula for choosing a discrete set of frequencies within a specified frequency band. A corresponding frequency weighting formula is added in order to maintain the same target impulse response in time-domain as the one achieved by dense uniform frequency sampling. Numerical and experimental results are presented to demonstrate the improved performances of the proposed sparse sampling method for SFCW radar imaging.

Python based Frequency Sampling Technique Algorithm for Hearing Impairment

Hearing is taken into account because the most vital senses of humans connects us to the world always and the communication between humans are mostly by speaking and listening. As per World Health Organization, 466 million People at Risk of the hearing impairment across the world. It adversely affects physical, behavioral, and social functions, as well as the general quality of live. The most task of the hearing aid is used to by selection amplify the audio sounds such the processed sound can be audible for hearing impairment. In this work, frequency sampling method is used to design a filter for hearing impairment. The proposed algorithm is implemented using python programming. The sound is categorized into two ways vowels and consonants. Vowels have low frequencies that means high pitch and are easier to hear. Consonants have higher frequencies and harder to hear. The changes in formants and pitch is observed which would be useful speech for hearing impaired.

Correction: Salarkaleji, M. Frequency and Polarization-Diversified Linear Sampling Methods for Microwave Tomography and Remote Sensing Using Electromagnetic Metamaterials. Electronics 2017, 6, 85

The authors would like to change the affiliation for second author, Mohammadreza Eskandari, as listed in the original version of the article [...]

A variable frequency sampling method for sudden small-volume data and conventional large-volume data

Data acquisition of manufacturing equipment and process is the foundation to achieve intelligent shop-floor. Due to the instantaneity and suddenness of sudden small-volume data (SSVData), sensitive perception and high frequency acquisition are necessary. However, continuous high frequency acquisition will result in a large amount of data, which brings great difficulties to data storage and analysis. Meanwhile, the existing low frequency acquisition for conventional large-volume data (CLVData) cannot meet the requirements of SSVData. Therefore, this paper systematically analyzes the differences and relationship between CLVData and SSVData, and investigates state-of-the-art of both in shop-floor. Then a novel variable frequency sampling method is proposed, which solves the contradiction between low frequency acquisition for CLVData and high frequency acquisition for SSVData.

Error Correction for FSI-Based System without Cooperative Target Using an Adaptive Filtering Method and a Phase-Matching Mosaic Algorithm

In our frequency scanning interferometry-based (FSI-based) absolute distance measurement system, a frequency sampling method is used to eliminate the influence of laser tuning nonlinearity. However, because the external cavity laser (ECL) has been used for five years, factors such as the mode hopping of the ECL and the low signal-to-noise ratio (SNR) in a non-cooperative target measurement bring new problems, including erroneous sampling points, phase jumps, and interfering signals. This article analyzes the impacts of the erroneous sampling points and interfering signals on the accuracy of measurement, and then proposes an adaptive filtering method to eliminate the influence. In addition, a phase-matching mosaic algorithm is used to eliminate the phase jump, and a segmentation mosaic algorithm is used to improve the data processing speed. The result of the simulation proves the efficiency of our method. In experiments, the measured target was located at eight different positions on a precise guide rail, and the incident angle was 12 degrees. The maximum deviation of the measured results between the FSI-based system and the He-Ne interferometer was 9.6 μm, and the maximum mean square error of our method was 2.4 μm, which approached the Cramer-Rao lower bound (CRLB) of 0.8 μm.