Two-way Array Research Articles

Design of Linear and Planar Arrays With Low Sidelobe Levels and High Directivity Using Two-Way Array Factor

Design of Linear and Planar Arrays With Low Sidelobe Levels and High Directivity Using Two-Way Array Factor

Lowering the Sidelobe Level of a Two-Way Pattern in Shared Aperture Radar Arrays

A study of lowering the peak SLL of shared aperture radar arrays is presented. A two-weight amplitude distribution for the elements of transmit and receive arrays is used. Imposing certain conditions, the relation of the number of elements of the arrays was found. One condition imposes the appearance of a minor lobe position of transmit or receive array pattern at a certain null of receive or transmit array pattern. A second condition imposes the equal sidelobe level of two consecutive minor lobes either near the main beam of the two-way array pattern or at certain positions of receive or transmit array pattern. The resulting peak SLL of the two-way radar array pattern depending on the conditions reaches from −47 dB up to less than −50 dB.

Design of Shared Aperture Radar Arrays With Low Sidelobe Level of the Two-Way Array Factor

A study to reduce the peak sidelobe level (SLL) of a radar two-way array factor is presented. It applies the condition that the first significant sidelobe of the transmitting array is in the same direction as the first null of the receiving array. Moreover, it is supposed that in the two-way array pattern, two consecutive sidelobes near the main beam become equal. Moving one step further, by combining the advantages of taper distribution and the simplicity of the feed network of uniform arrays, a two-weight amplitude distribution for the radar transmit and receive arrays is designed. The resulting peak SLL of the two-way pattern becomes less than −45 dB.

Lowering the Sidelobe Level of a Two-Way Array Factor for an Array With Uniform Transmit and Uniform Receive Arrays

A two-way array factor is the product of the transmit array factor and the receive array factor of a radar. Lowering the sidelobe level (SLL) of the two-way pattern traditionally requires amplitude tapering the transmit and receive apertures. This communication demonstrates the two-way pattern sidelobe reduction using only uniform transmit and receive apertures. If both array factors are uniform, then the expected peak two-way SLL is a little less than −27 dB. This level can be reduced without amplitude tapering if the receive array is made smaller by turning off edge elements. This communication demonstrates this idea for uniform linear and planar arrays. An additional 6.7 dB reduction is possible for the two-way maximum SLL.

A low-cost wideband phase shifter for two-way mm-wave phased array antenna system

This paper presents a wideband, low-cost, high-performance, and continuous phase shifter for millimeter-wave (mm-wave) phased array systems. Its operational principle is based on modifying the propagation mode of a grounded coplanar waveguide (GCPW) line by placing a high dielectric constant slab over the GCPW line. The propagation constant and hence the phase shift is varied by changing the air gap height between the GCPW line and the dielectric slab. As a proof of concept, a piezoelectric transducer is used to precisely control this air gap height. A printed circuit board-based phase shifter prototype has been designed, fabricated, and tested at two different frequency bands (19–21 and 28.5–30.5 GHz), which are the downlink and uplink bands, respectively, of the Ka-band two-way satellite communication system. A continuous and almost linear phase–voltage characteristic has been achieved experimentally with average phase shift variations 170° and 260° over the two bands, respectively. The footprint of the proposed phase shifter is 2.1 mm×3 mm, which is quite small and suitable for low-profile mm-wave applications. The average insertion losses over the two bands are <0.53 and 2.35 dB with very low variations±0.22 and ±0.35 dB, respectively.

Multivariate curve resolution alternating least square (MCR-ALS) analysis on total synchronous fluorescence spectroscopy (TSFS) data sets: Comparing certain ways of arranging TSFS-based three-way array

Total synchronous fluorescence spectroscopy (TSFS)-based three-way array sample×excitation wavelength×Δλ has inherently complex data structure. Multivariate curve resolution alternating least square (MCR-ALS) analysis is a soft mathematical modelling technique that can be used to retrieve pure spectral and contribution profile of the fluorophores of a multifluorophoric mixture provided it is applied to bilinear data sets. In the present work, possibilities of generating bilinear two-way arrays by (i) unfolding and (ii) augmenting the TSFS-based three-way array were studied. Bilinear characteristics of the obtained two-way arrays were tested by subjecting them to MCR-ALS analysis. It was found that lack of analytical–mathematical relationship between spectral profile along the excitation wavelength mode and the offset mode do not allow the application of MCR-ALS analysis on augmented TSFS data set. Moreover, the augmentation procedure and chemical-mathematical rank of the subsequently obtained data sets were found to be ‘not independent’ of each other. Two-way array sample×(excitation wavelength×Δλ) obtained by unfolding TSFS-based three-way array along the sample mode was found to have symmetrical structure, i.e., both sample mode and spectral mode have equal mathematical and chemical rank making them highly attuned to MCR-ALS analysis.

Cross-classified sampling: Some estimation theory

For a population represented as a two-way array, we consider sampling via the product of independent row and column samples. Theory is presented for the estimation of a population total under alternative methods of sampling the rows and columns.

Multi-way analysis for decadal pollution trends assessment: The Guadalquivir River estuary as a case study

Alongside history, human activities have contributed to the deployment of environmental quality. In particular, during the last decades the problem of water preservation has gained increasing attention.Statistical analysis is essential to analyze environmental data and to identify trends of pollutants over space and time. Usually applied techniques for data treatment are based on the organization of data in a two-way array, missing some shades on pollutants distribution. This fact supports the use of multi-way techniques, which allow the analysis of the results through different directions at the same time. For Three Modes Principal Components Analysis (3MPCA) a principal components analysis is conducted using three modes and a “core” matrix that allows assessing their interactions. In the case of environmental studies, it offers information about the spatial–temporal evolution of pollutants in a certain water body.The Guadalquivir River estuary has been used as a model system. It is a representative human influenced system, where different pollution inputs have been characterized. In this study, decadal evolution of pollutants has been discussed, to evaluate among others the effects of EU legislation on river water quality.The aim of this work is the establishment of the evolution, during the last decade, of nutrients and metals ultra-traces distribution in an estuary affected by anthropic activities. As examples, Pb and PO43− show a trend to decrease their weight on water pollution, total suspended solids (TSS) behavior is related with massive rain events, and the rising of new technologies appears as a source of emerging pollutants as Co in urban-industrial areas.

Speaker Adaptation Based on PPCA of Acoustic Models in a Two-Way Array Representation

Speaker Adaptation Based on PPCA of Acoustic Models in a Two-Way Array Representation

Disentangling Dynamic Changes of Multiple Cellular Components during the Yeast Cell Cycle by in Vivo Multivariate Raman Imaging

Cellular processes are intrinsically complex and dynamic, in which a myriad of cellular components including nucleic acids, proteins, membranes, and organelles are involved and undergo spatiotemporal changes. Label-free Raman imaging has proven powerful for studying such dynamic behaviors in vivo and at the molecular level. To construct Raman images, univariate data analysis has been commonly employed, but it cannot be free from uncertainties due to severely overlapped spectral information. Here, we demonstrate multivariate curve resolution analysis for time-lapse Raman imaging of a single dividing yeast cell. A four-dimensional (spectral variable, spatial positions in the two-dimensional image plane, and time sequence) Raman data "hypercube" is unfolded to a two-way array and then analyzed globally using multivariate curve resolution. The multivariate Raman imaging thus accomplished successfully disentangles dynamic changes of both concentrations and distributions of major cellular components (lipids, proteins, and polysaccharides) during the cell cycle of the yeast cell. The results show a drastic decrease in the amount of lipids by ~50% after cell division and uncover a protein-associated component that has not been detected with previous univariate approaches.

Flow rate measurement of individual oil well using multivariate thermal analysis

Flow measurement of individual oil wells mainly consisted of using test-separator units with many limitations including time and cost consuming, uncertainty of well isolation, and need to closing the co-line wells. The multivariate regression of thermogravimetric data were used to predict the accurate productivity of oil wells using a single sample-point at the blend-oil pipe-line. The results revealed that the Weighted Sum Model was appropriate for oils, which their thermal traces were significantly different from each other. The thermogravimetric data was arranged in a two-way array by taking the number of oil samples and the thermal signal intensities as columns and rows, respectively. The data matrix was decomposed using the commend of Matrix Left Division in MATLAB and the rank of individual oil wells was determined as a column vector. The error vector corrected the blend equation by considering the catalytic pyrolysis and eutectic point in higher and lower temperatures, respectively. The model predicted the accurate productivity of individual oil wells in an offshore oil field after 2010.

Spectroscopic studies of the interaction between pirimicarb and calf thymus DNA

The interaction between pirimicarb and calf thymus DNA in physiological buffer (pH 7.4) was investigated with the use of Neutral Red (NR) dye as a spectral probe by UV–vis absorption, fluorescence and circular dichroism (CD) spectroscopy, as well as viscosity measurements and DNA melting techniques. The results revealed that an intercalation binding should be the interaction mode of pirimicarb to DNA. CD spectra indicated that pirimicarb induced conformational changes of DNA. The binding constants of pirimicarb with DNA were obtained by the fluorescence quenching method. The thermodynamic parameters, enthalpy change (Δ H θ ) and entropy change (Δ S θ ) were calculated to be −52.13 ± 2.04 kJ mol −1 and −108.8 ± 6.72 J mol −1 K −1 according to the van’t Hoff equation, which suggested that hydrogen bonds and van der Waals forces might play a major role in the binding of pirimicarb to DNA. Further, the alternative least squares (ALS) method was applied to resolve a complex two-way array of the absorption spectra data, which provided simultaneously the concentration information for the three reaction components, pirimicarb, NR and DNA–NR. This ALS analysis indicated that the intercalation of pirimicarb into the DNA by substituting for NR in the DNA–NR complex.

Study of interaction between kaempferol–Eu 3+ complex and DNA with the use of the Neutral Red dye as a fluorescence probe

The interaction between kaempferol–Eu 3+ complex and calf thymus DNA was investigated in physiological buffer (pH 7.4) using the Neutral Red (NR) dye as a spectral probe by UV–vis absorption and fluorescence spectroscopy, as well as viscosity measurements and DNA melting techniques. The results indicated that kaempferol–Eu 3+ complex can bind to DNA and the major binding mode is intercalative binding. The binding constants K and number of binding sites n of kaempferol–Eu 3+ complex with DNA were obtained by fluorescence quenching method. The thermodynamic parameters (Δ H θ , Δ S θ and Δ G θ ) were calculated from the fluorescence data measured at three different temperatures, which showed that the binding of kaempferol–Eu 3+ complex to DNA was driven mainly by hydrophobic interaction. Furthermore, the alternative least squares (ALS) method was applied to resolve a complex two-way array of the absorption spectra data, which provided simultaneously the concentration information for the three reaction components, NR, kaempferol–Eu 3+ and DNA–NR. This ALS analysis indicated that the intercalation of the kaempferol–Eu 3+ complex into the DNA proceeds by exchanging with the NR probe.

Interaction between quercetin–copper(II) complex and DNA with the use of the Neutral Red dye fluorophor probe

The interaction of quercetin–Cu(II) complex with calf thymus DNA was investigated with the use of Neutral Red (NR) dye as a spectral probe by the application of UV–vis spectrophotometry, cyclic voltammetry and synchronous fluorescence spectroscopy. The results showed that both quercetin–Cu(II) complex and the NR molecule can intercalate into the double helix of the DNA. The 2:1 quercetin:Cu(II) complex (estimated binding constant = 2.85 × 10 9) is stabilized by intercalation in the DNA (binding constant, K [quercetin–Cu(II)–DNA] = (1.82 ± 0.20) × 10 5 M −1), and displaces the NR dye from the NR–DNA complex in a competitive reaction. Cyclic voltammetry studies confirm the intercalation reaction and show that the ratio ( K R/ K O) of binding constants for the reduced and oxidized forms of the metal complex is 2.05. Furthermore, the alternative least squares (ALS) method was applied to resolve a complex two-way array of the absorption spectra data. This yielded the equilibrium concentration profiles of each component in the reaction (NR, NR–DNA and quercetin–Cu(II)) as well as the corresponding pure spectra. The extracted profiles showed that at equilibrium the [NR–DNA] and [NR] trends decreased and increased symmetrically, respectively, with approximately linear behaviour being observed below 10 × 10 −6 mol L −1 of the added quercetin–Cu 2+ complex. Thereafter, these trends converged asymptotically. The free [quercetin–Cu(II)] trend-line at equilibrium was linear over the whole range of the complex added. It was possible to estimate the approximate value of the equilibrium constant of the exchange process (approximately 5 × 10 −1) involving the intercalation of the quercetin–Cu(II) complex. It was also found that about 35% of the bound complex was unaccounted by the intercalation reaction, presumably being stabilized at an alternative site.

The asymptotic distribution of the constant behavior of the generalized partial autocorrelation function of an ARMA process

The two-way array of the generalized partial autocorrelations (GPAC's) of an autoregressive moving-average (ARMA) model shows a constant behavior and a zero behavior, which are useful for ARMA model identification. In this paper the asymptotic joint distribution of the GPAC estimators of the constant behavior is derived, which shows the corresponding asymptotic variance increases geometrically as the lag does.

SIMULATIONS AND DERIVED APPROXIMATIONS FOR THE MEANS AND STANDARD DEVIATIONS OF THE CHARACTERISTIC ROOTS OF A WISHART MATRIX

Monte Carlo simulations were done to estimate the means and standard deviations of the characteristic roots of a Wishart matrix which can be used in computing tests of hypotheses concerning multiplicative terms in balanced linear-bilinear (multiplicative) models for an m × n table of data. In this report we extend the previous results (Mandel, 1971; Cornelius, 1980) to r ≤ 199, c ≤ 149 or r ≤ 149, c ≤ 199, where r and c are row and column degrees of freedom, respectively, of the two-way array of residuals (with total degrees of freedom rc) after fitting the linear effects. For 187 combinations of r and c at intervals over this domain, we used 5000 simulations to estimate expectations and standard deviations of the Wishart roots. Using weighted linear regression variable selection techniques, symmetric functions of r and c were obtained for approximating the simulated means and standard deviations. Use of these approximating functions will avoid the need for reference to tables for input to computer programs which require these values for tests of significance of sequentially fitted terms in the analyses of balanced linear-bilinear models.

Estimating rate constants and pure UV-vis spectra of a two-step reaction using trilinear models

This paper describes the estimation of reaction rate constants and pure species UV-vis spectra of the consecutive reaction of 3-chlorophenylhydrazonopropane dinitrile with 2-mercaptoethanol. The reaction rate constants were estimated from the UV-vis measurements of the reacting system using the generalized rank annihilation method (GRAM) and the Levenberg-Marquardt/PARAFAC (LM-PAR) algorithm. Both algorithms can be applied in cases where the contribution of different species in the mixture spectra is of exponentially decaying character. From a single two-way array, two two-way datasets are formed by means of splitting such that there is a constant time lag between the two two-way datasets. By stacking these two two-way datasets, the reaction rate constants can be estimated very easily from the third dimension. GRAM, which is fast and non-iterative, decomposes the trilinear structure using a generalized eigenvalue problem (GEP). The iterative algorithm LM-PAR consists of a combination of the Levenberg-Marquardt algorithm and alternating least squares steps of the PARAFAC model using GRAM results as a set of initial starting values. Pure spectra of the absorbing species were estimated and compared with their measured pure spectra. LM-PAR performed the best, giving the lowest relative fit error. However, the relative fit error obtained with GRAM was acceptable. Since a lot of measurements are based on exponentially decaying functions, GRAM and LM-PAR can have many applications in chemistry. Copyright (C) 1999 John Wiley & Sons, Ltd

An algorithm for weighted bilinear regression

Bilinear models in which the expectation of a two-way array is the sum of products of parameters are widely used in spectroscopy. In this paper we present an algorithm called combined-vector successive overrelaxation (COV-SOR) for bilinear models, and compare it with methods like alternating least squares, singular value decomposition, and the Marquardt procedure. Comparisons are done for missing data also.

Perfectly overlapped merging and sorting on a two-way linear array

We present a perfectly overlapped merging algorithm, which can require almost only input time to perform merge sorting on a linear array of processors. The optimal merge order that minimizes the merge sorting time is obtained in constant time. The merging algorithm and a previously proposed runs-generation algorithm can serve for sorting a very large file; the time complexity of the resulting algorithm is optimal under the hardware condition.

The Analysis of Multivariate Contingency Tables by Restricted Canonical and Restricted Association Models

Abstract Restricted canonical models and restricted association models are proposed and applied to multiway contingency tables. These models have been previously applied to two-way contingency tables; however, multivariate generalization has been impeded in the past, since canonical and association models both depend on singular value decompositions that apply only to two-way arrays. In this article, this restriction to two-way arrays is overcome by division of the cross-classified variables into explanatory and response variables. The explanatory variables are treated as a single polytomous variable, and the response variables are treated as a second single polytomous variable. In this fashion, the multiway table is reduced to a two-way array to which traditional canonical and association models may be applied. Use of linear restrictions on parameters in canonical and association models is especially important in multiway tables if useful models are to be constructed. The class of models considered in this article is sufficiently broad to include models of conditional independence, homogeneity models, conditional symmetry models, log-linear models of no three-factor interaction, conditional quasisymmetry models, and models that express association in terms of preassigned scores. The proposed models can be applied to tables in which some or all variables are ordered as well as to tables with no ordered variables. To illustrate results, appropriate restricted canonical and restricted association models are applied to a three-way cross-classification of abortion attitudes (a response variable) and religion and education (explanatory variables). Insights into the table are obtained that are not readily available from the analysis of Haberman (1979, chap. 6).