scholarly journals Passive Localization of 3D Near-Field Cyclostationary Sources Using Parallel Factor Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jian Chen ◽  
Guohong Liu ◽  
Xiaoying Sun
Keyword(s):  
Near Field ◽  
Three Dimensional ◽  
Least Squares Regression ◽  
Localization Algorithm ◽  
Analysis Model ◽  
Third Order ◽  
Multidimensional Search ◽  
Satisfactory Performance ◽  
Parallel Factor ◽  
Passive Localization

By exploiting favorable characteristics of a uniform cross-array, a passive localization algorithm of narrowband cyclostationary sources in the spherical coordinates (azimuth, elevation, and range) is proposed. Firstly, we construct a parallel factor (PARAFAC) analysis model by computing the third-order cyclic moment matrices of the properly chosen sensor outputs. Then, we analyze the uniqueness of the constructed model and obtain three-dimensional (3D) near-field parameters via trilinear alternating least squares regression (TALS). The investigated algorithm is well suitable for the localization of the near-field cyclostationary sources. In addition, it avoids the multidimensional search and pairing parameters. Results of computer simulations are carried out to confirm the satisfactory performance of the proposed method.

scholarly journals Joint 2D Direction-of-Arrival and Range Estimation for Nonstationary Sources

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Jian Chen ◽  
Hui Zhao ◽  
Xiaoying Sun ◽  
Guohong Liu
Keyword(s):  
Factor Analysis ◽  
Near Field ◽  
Direction Of Arrival ◽  
Parallel Factor Analysis ◽  
Observation Data ◽  
Factor Analysis Model ◽  
Time Frequency ◽  
Multidimensional Search ◽  
Parallel Factor ◽  
Nonstationary Sources

Passive localization of nonstationary sources in the spherical coordinates (azimuth, elevation, and range) is considered, and a parallel factor analysis based method is addressed for the near-field parameter estimation problem. In this scheme, a parallel factor analysis model is firstly constructed by computing five time-frequency distribution matrices of the properly chosen observation data. In addition, the uniqueness of the constructed model is proved, and both the two-dimensional (2D) direction-of-arrival (DOA) and range can be jointly obtained via trilinear alternating least squares regression (TALS). The investigated algorithm is well suitable for near-field nonstationary source localization and does not require parameter-pairing or multidimensional search. Several simulation examples confirm the effectiveness of the proposed algorithm.

Modeling and experimental verification on directivity of an electret cell array loudspeaker

2012 ◽  
Vol 24 (3) ◽  
pp. 326-333 ◽  
Author(s):  
Yu-Chi Chen ◽  
Wen-Ching Ko ◽  
Han-Lung Chen ◽  
Hsu-Ching Liao ◽  
Wen-Jong Wu ◽  
...  
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Three Dimensional ◽  
Digital Control System ◽  
Analysis Model ◽  
Cell Array ◽  
Element Analysis ◽  
Finite Element Analysis Model ◽  
The Finite Element Analysis ◽  
Directivity Characteristics

We propose a model to give us a method to investigate the characteristic three-dimensional directivity in an arbitrarily configured flexible electret-based loudspeaker. In recent years, novel electret loudspeakers have attracted much interest due to their being lightweight, paper thin, and possessing excellent mid- to high-frequency responses. Increasing or decreasing the directivity of an electret loudspeaker makes it excellent for adoption to many applications, especially for directing sound to a particular area or specific audio location. Herein, we detail a novel electret loudspeaker that possesses various directivities and is based on various structures of spacers instead of having to use multichannel amplifiers and a complicated digital control system. In order to study the directivity of an electret loudspeaker based on an array structure which can be adopted for various applications, the horizontal and vertical polar directivity characteristics as a function of frequency were simulated by a finite-element analysis model. To validate the finite-element analysis model, the beam pattern of the electret loudspeaker was measured in an anechoic room. Both the simulated and experimental results are detailed in this article to validate the various assertions related to the directivity of electret cell-based smart speakers.

scholarly journals Imaging of bi-anisotropic periodic structures from electromagnetic near-field data

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Dinh-Liem Nguyen ◽  
Trung Truong
Keyword(s):  
Inverse Scattering ◽  
Maxwell Equations ◽  
Field Data ◽  
Periodic Structures ◽  
Near Field ◽  
Scattering Problem ◽  
Three Dimensional ◽  
Inverse Scattering Problem ◽  
Factorization Method ◽  
Unique Determination

AbstractThis paper is concerned with the inverse scattering problem for the three-dimensional Maxwell equations in bi-anisotropic periodic structures. The inverse scattering problem aims to determine the shape of bi-anisotropic periodic scatterers from electromagnetic near-field data at a fixed frequency. The factorization method is studied as an analytical and numerical tool for solving the inverse problem. We provide a rigorous justification of the factorization method which results in the unique determination and a fast imaging algorithm for the periodic scatterer. Numerical examples for imaging three-dimensional periodic structures are presented to examine the efficiency of the method.

scholarly journals Efficient Localization Algorithm for Near-Field Noncircular Sources via Dual-Polarization Sensor Array

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Jiaqi Song ◽  
Haihong Tao
Keyword(s):  
Source Localization ◽  
Near Field ◽  
Nuisance Parameter ◽  
Estimation Accuracy ◽  
Localization Algorithm ◽  
Dual Polarization ◽  
Rank Reduction ◽  
Localization Accuracy ◽  
Noncircular Signals ◽  
Polarization Sensor

Noncircular signals are widely used in the area of radar, sonar, and wireless communication array systems, which can offer more accurate estimates and detect more sources. In this paper, the noncircular signals are employed to improve source localization accuracy and identifiability. Firstly, an extended real-valued covariance matrix is constructed to transform complex-valued computation into real-valued computation. Based on the property of noncircular signals and symmetric uniform linear array (SULA) which consist of dual-polarization sensors, the array steering vectors can be separated into the source position parameters and the nuisance parameter. Therefore, the rank reduction (RARE) estimators are adopted to estimate the source localization parameters in sequence. By utilizing polarization information of sources and real-valued computation, the maximum number of resolvable sources, estimation accuracy, and resolution can be improved. Numerical simulations demonstrate that the proposed method outperforms the existing methods in both resolution and estimation accuracy.

scholarly journals A Four-point three-dimensional spatial localization algorithm based on RSSI

2020 ◽  
Vol 1550 ◽  
pp. 032022
Author(s):  
Li Ma ◽  
Ning Cao ◽  
Minghe Mao ◽  
Jianping Zhang
Keyword(s):  
Three Dimensional ◽  
Spatial Localization ◽  
Localization Algorithm

scholarly journals Investigating microcrystalline cellulose crystallinity using Raman spectroscopy

Cellulose ◽  
2021 ◽  
Author(s):  
Ana Luiza P. Queiroz ◽  
Brian M. Kerins ◽  
Jayprakash Yadav ◽  
Fatma Farag ◽  
Waleed Faisal ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Microcrystalline Cellulose ◽  
Web Application ◽  
Principal Component ◽  
Raw Material ◽  
Least Squares Regression ◽  
Analysis Model ◽  
General Reference ◽  
Material Source ◽  
Univariate Model

AbstractMicrocrystalline cellulose (MCC) is a semi-crystalline material with inherent variable crystallinity due to raw material source and variable manufacturing conditions. MCC crystallinity variability can result in downstream process variability. The aim of this study was to develop models to determine MCC crystallinity index (%CI) from Raman spectra of 30 commercial batches using Raman probes with spot sizes of 100 µm (MR probe) and 6 mm (PhAT probe). A principal component analysis model separated Raman spectra of the same samples captured using the different probes. The %CI was determined using a previously reported univariate model based on the ratio of the peaks at 380 and 1096 cm−1. The univariate model was adjusted for each probe. The %CI was also predicted from spectral data from each probe using partial least squares regression models (where Raman spectra and univariate %CI were the dependent and independent variables, respectively). Both models showed adequate predictive power. For these models a general reference amorphous spectrum was proposed for each instrument. The development of the PLS model substantially reduced the analysis time as it eliminates the need for spectral deconvolution. A web application containing all the models was developed. Graphic abstract

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