Difference In Frequency Domain Research Articles

Research on infrared dim and small target detection algorithm based on frequency domain difference

ABSTRACT The high accuracy of infrared dim and small target detection in complex backgrounds is of great relevance for infrared identification and tracking systems. Traditional infrared dim and small target detection methods suit scenes with a single and homogeneous continuous background. However, human vision system methods suffer from an undetectable or high false alarm rate in complex scenes with dim small targets. To address this shortcoming, this paper proposes an infrared dim and small target detection algorithm based on frequency domain differencing (FDD). The proposed algorithm consists of a spectrum residual module and a Gaussian greyscale difference module. Firstly, the target enhancement image is constructed by using the spectrum residual module to highlight small targets and suppress background noise. Secondly, the local contrast of the image is enhanced by the Gaussian grayscale difference module, which accurately depicts the edge information of small targets and locates them. Finally, the target enhancement image and Gaussian grayscale difference image are fused to detect infrared dim and small targets. Experimental results show that the proposed algorithm has higher accuracy under the evaluation metrics of local signal-to-noise ratio gain (LSNRG), signal-to-clutter ratio gain (SCRG) and background suppression factor (BSF). At the same time, compared with other algorithms, the detection rate of the proposed algorithm is higher for infrared dim and small targets in complex scenes. Code is available at https://github.com/m156879/FDD-module.

Quantitative analysis of FQs antibiotics content in FMF using THz spectral and imaging technology

Rapid and accurate detection of fluoroquinolones (FQs) antibiotics residues in food substrate are of great significance to food safety. In this study, terahertz spectroscopy was employed to conduct the spectral and imaging analysis to explore its feasibility for detection concentrations of FQs in fish meal feeds (FMF). Four methods (frequency of maximum difference in frequency-domain, characteristic absorption peak, successive projections algorithm and stepwise regression) were used to selected characteristic frequencies of sample. Terahertz imaging was formed at selected characteristic frequency and back propagation neural network was used to establish quantitative evaluation models to select optimal characteristic imaging frequency. Finally, relationship between concentrations of FQs and their gray values was revealed, and each data had a small range of error bar. The results showed that terahertz spectral and imaging technique can visualize norfloxacin and enrofloxacin concentrations in FMF precisely. This study explored a brand-new visualization method for quantitative detection of FQs in FMF based on terahertz spectral and imaging technology.

Intelligent recognition of acoustic emission signals from damage of glass fiber-reinforced plastics

Glass fiber-reinforced plastics (GFRP) is widely used in many industrial fields. When acoustic emission (AE) technology is applied for dynamic monitoring, the interfering signals often affect the damage evaluation results, which significantly influences industrial production safety. In this work, an effective intelligent recognition method for AE signals from the GFRP damage is proposed. Firstly, the wavelet packet analysis method is used to study the characteristic difference in frequency domain between the interfering and AE signals, which can be characterized by feature vector. Then, the model of back-propagation neural network (BPNN) is constructed. The number of nodes in the input layer is determined according to the feature vector, and the feature vectors from different types of signals are input into the BPNN for training. Finally, the wavelet packet feature vectors of the signals collected from the experiment are input into the trained BPNN for intelligent recognition. The accuracy rate of the proposed method reaches to 97.5%, which implies that the proposed method can be used for dynamic and accurate monitoring of GFRP structures.

Estimating geometrical parameters of cylindrical targets detected by ground-penetrating radar using template matching algorithm

In the current research, the ground-penetrating radar (GPR) method has been employed to identify physical and geometrical parameters of buried cylindrical structures using the pattern recognition approach. To achieve this goal, the well-established mathematical relationships between geometrical parameters of cylindrical target (radius, burial depth, and horizontal location) and the associated GPR hyperbolic response characteristics are employed using the template matching method. In order to validate the applicability of the template matching method in providing estimates of such parameters, the method is first examined on GPR responses of synthetic models with known geometrical parameters followed by applying on real data using two different similarity criteria including 2-D spatial convolution and normalized cross correlation in the wave number domain. In the first step, the GPR responses of 71 synthetic models encompassing one, two, and three horizontal cylinders were produced using the improved 2-D finite difference in frequency domain. Then, appropriate preprocessing sequences to reduce random noise caused by forward modeling were applied on synthetic data. The proposed algorithm applied on several synthetic model responses could estimate the known geometrical parameters of the buried cylinders with acceptable accuracy (maximum error of 15%). The template matching algorithm was also used to extract geometrical parameters of water and wastewater pipes buried in Imam Hossein Square, Isfahan city, as real GPR data. Depending on environmental conditions and subsurface host formation, the real GPR data normally contain a variety of noises; therefore, a series of appropriate objective preprocessing and processing stages were designed in order to apply on real GPR images before deploying template matching algorithm. The applicability of the template matching algorithm on real data and validity of the estimated parameters were proved based on assessing the accuracy of the estimated geometrical parameters of respective pipes through GPR response versus the measured parameters. The proposed algorithm was designed in such a way that all steps of estimating geometrical parameters of buried cylindrical targets are automatically carried out.

Numerical study of mean flow effect on sound propagation through an aerosol

Previous studies on the sound attenuation and dispersion in an aerosol consisting of air and water droplets have been extended to accommodate mean flow effects. A numerical methodology based on solution of one dimensional, linearized Euler equations in the frequency domain has been developed. The interactions between the fluid and particle phases have been considered to be through Stokesian drag force. First, the verification of the numerical code has been shown for the zero mean flow case with comparative evaluation of results available in literature. Next, the attenuation and dispersion results of both upstream and downstream flows have been presented. The comparison of results suggests that significant deviations exist for attenuation values between the stationary and the mean flow cases at the same frequencies. Keywords: Suspension Acoustics, Finite Difference in Frequency Domain (FDFD), Mean Flow Effect

The influence of plasmonic and dielectric inclusions on antireflective properties of homogeneous coatings for silicon photovoltaic structures

Subject of Study. Theoretical analysis of the efficiency for the antireflective coatings based on plasmonic silver (Ag) and dielectric silicon (Si) nanoparticles is presented. We observe the increase of light absorption in the active layer, which is related to the optical resonant properties of considered nanoparticles. Characteristic property of the studied composite layer is its ability to combine the functions of electric contacts and anti-reflective coating. Method. Numerical calculations were performed in CST Microwave Studio with FDFD method (Finite Difference in Frequency Domain). The optical parameters of materials were extracted from the experimentally measured data available in literature. Geometrical parameters of composite layer – size and location of particles – were varied. Comparison of light absorption efficiency for different coatings on top of the active layer is presented: the homogeneous Indium Tin Oxide (ITO) layer, ITO layer with the spherical nanoparticle inclusions on the ITO surface, ITO layer with spherical nanoparticle bulk inclusions. Periodical lattices of particles with sizes of range between 15 and 80 nm were considered. Nanoparticles of this size have dominant dipole response. Main Results. Numerical calculations have shown that nanoparticle inclusions cause significant deformation of the absorption spectra with appearing of resonant pecularities in the wavelength range equal to 300-800 nm. It originates from the nanoparticle resonant features, which are similar to the resonant features of isolated nanoparticles. Absorption in the active layer decreases sharply at the resonant wavelength. Resonant response of nanoparticles placed on the ITO surface differs significally from the isolated ones: the resonant frequency and Q-factor decrease. It was shown that absorption in the active layer decreases by 25 % when the size of Ag and Si particles increases. Ag nanoparticles, placed in ITO layer on top of the active layer, show a monotonic decrease of integral absorption down to 30% with decreasing of nanoparticle size. Si nanoparticles of 50 nm radius have maximal influence on the absorption. Practical Significance. These results may be useful for understanding the physics of antireflective composite coatings with inclusions of nanoparticles for developers of silicon solar cells.

Real-time unstart prediction and detection of hypersonic inlet based on recursive Fourier transform

Unstart is an abnormal operation, and special care is devoted to this phenomenon for a hypersonic inlet. The process of a two-dimensional hypersonic inlet from start to unstart is experimentally demonstrated by recording the corresponding time history of the wall static pressure. By analyzing the pressure signals, it can be found that the oscillation of shock train flow can be used to characterize the location of shock train leading-edge. The register of shock train leading-edge at T14 located close to inlet throat is a good precursor for unstart prediction. T8 located in the upstream of last ramp compression shock is the optimum transducer for unstart detection because its pressure just goes through steady flow and unstart flow. Based on the differences in frequency domain among steady flow, shock train flow and unstart flow, recursive Fourier transform for unstart prediction and detection is introduced. The algorithm description, algorithm application, and parameters influence of the detection method are discussed, and the results show the validity of the detection method.

A quick diagnostic test for NMR receiver gain compression

Modern NMR spectrometers require receivers to work within their linear ranges to maintain high fidelity line shape and peak integration. For better sensitivity, the receiver gain has to be optimized to detect dilute analytes; however, gain compression needs to be avoided. Here, we explore if and how linear receiver performance can be achieved for a couple of representative gain settings on a spectrometer. In the case of slight receiver gain compression, not only will the peak integral be attenuated but a very small line-shape change can also be observed. Hence, we can resort to resonance integration and line-shape analysis for gain compression diagnosis. As such, NMR signals, regardless of their observed amplitude difference in frequency domain, can be accurately compared in quantitative analysis.

Membrane-supported coplanar waveguides for MMIC and sensor application

Membrane-supported coplanar waveguides (CPWs) are needed for low-dispersive and low-loss millimeter- and submillimeter waves as well as for power sensor applications. The authors demonstrate CPWs on polyimid membranes micromachined on gallium arsenide (GaAs) that meet the requirements of a typical microwave monolithic integrated circuit (MMIC) process. The influence of the design parameters is simulated by finite difference in frequency domain (FDFD), in excellent agreement with the experiment. For a membrane CPW with ground to ground spacing of only 50 /spl mu/m and characteristic impedance of 115 /spl Omega/, relative effective dielectric constants near 1.02 and attenuation of 0.14 dB/mm at 25 GHz have been achieved.