One-dimensional Peak Research Articles

Quasi Elastic Neutron Scattering model library

This paper reports on the development of a collection of dynamical models of one-dimensional peak profile functions used to fit dynamic structure factors S (Q, ħω) of Quasi Elastic Neutron Scattering (QENS) data. The objective of this development is to create a maintainable and interoperable Python library with models reusable in other projects related to the analysis of data from Quasi Elastic Neutron Scattering experiments. The ambition is that the library also will serve as a platform where scientists can make their models available for others. We illustrate how the library can be used by newcomers to the field as well as by experts via different examples. These examples, provided as Jupyter notebooks, show how the QENS models can be integrated in the whole QENS data processing pipeline.

3-D temporal-spatial-based near-field source localization considering amplitude attenuation

A three-dimensional (3-D) localization algorithm for multiple near-field (NF) sources considering amplitude attenuation is proposed in this paper. Firstly, we use the symmetry of the array and the delay autocorrelation of NF signals to construct the virtual received data, whose phase factor is linear with the sensor position. By using the symmetry of amplitude attenuation of the virtual received data, a one-dimensional (1-D) peak search estimator is constructed to obtain the first angle parameter. Then, the estimated result is substituted into another spectral peak search function based on the original data to estimate the range parameter. Finally, a single-snapshot virtual received data set is generated, and the remaining angle parameter is solved by a phase retrieval operation. The proposed algorithm can automatically match the 3-D parameters, and has a stable estimation performance considering amplitude attenuation, as demonstrated by simulation results.

Parameter Estimation of Non-Gaussian Signals for Polarization-Sensitive Augmented Coprime Array: Fourth-Order Cumulant Reduced-Dimensional Capon Algorithm

In this paper, we investigate the problem of direction of arrival (DOA) and polarization estimation for non-Gaussian signal in polarization-sensitive augmented coprime array. Instead of the second-order cumulant statistics, the fourth-order cumulant statistics of the received signals are used for parameter estimation because they can detect more information of the non-Gaussian signal. First, polarization-sensitive augmented coprime array is designed, where each sensor element is equipped with a pair of orthogonal electric dipoles. Furthermore, a low-complexity reduced-dimensional Capon algorithm which uses the fourth-order cumulant of the received array signal is proposed for DOA and polarization estimation. Only one-dimensional peak search is required by reconstructing peak search function. Theoretical analysis has proven the effectiveness of the algorithm, and simulation results demonstrate that the proposed fourth-order cumulant reduced-dimensional Capon algorithm outperforms the other algorithms.

LP-DSPE Algorithm for Angular Parameter Estimation of Coherently Distributed Sources

The distributed source parameter estimator (DSPE) is one of the well-known angular parameter estimation techniques for coherently distributed sources. However, the computational cost of DSPE is not attractive due to the two-dimensional spectrum peak search. To overcome this problem, this letter proposes a novel DSPE algorithm based on compressive sensing theory, named as LP-DSPE algorithm. In the proposed method, at first, the nominal direction of arrival (DOA) estimation can be transformed into a linear programming problem through sparse recovery theory, whose feasible solution set is further expanded to improve the estimation accuracy. Then the angular spread can be obtained via a one-dimensional peak search utilizing the estimated nominal DOA. Compared with the previous works, the proposed algorithm can offer more accurate parameter estimation performance with lower computational complexity, even if in large angular spread scenarios. Theoretical analysis and simulation results demonstrate the performance of the proposed approach.

A Low Complexity DOA Estimation Method of CD Sources in Impulsive Noise

Direction of arrival (DOA) estimation, as the main technology of passive radio monitoring and positioning, has been deeply investigated. However, the DOA for distributed sources is challenging to estimate in environments with impulsive noise. Although many methods have been proposed for DOA estimation, most of them assume that array output signals contain Gaussian noise. Therefore, the performance of these methods is often poor for alpha-stable distributed impulsive noise. Furthermore, subspace-based DOA estimation methods for distributed sources require a two-dimensional (2D) peak search, which increases the consumption of system computing resources. In this paper, a Q-function-based kernel function is proposed, and its properties are derived. On this basis, a novel DOA estimation method is proposed for coherently distributed (CD) sources in impulsive noise. To reduce computational complexity, a Lagrangian quadratic optimization function is derived by approximating the generalized array manifold of the CD source. By solving this optimization function, a 2D peak search can be reduced to several one-dimensional (1D) peak searches. The simulation results illustrate that the accuracy and robustness of the proposed method outperform those of existing methods.

Two-Dimensional Direction-of-Arrival and Polarization Parameter Estimation Using Parallel Co-Prime Polarization Sensitive Array

Target detection is critical in many mission critical sensors and sensor network (MC-SSN) applications. For target detection in complicated electromagnetic environment, DOA estimation using polarization sensitive array (PSA) has been receiving increased attentions. In this paper, we propose the parallel co-prime polarization sensitive array (PCP-PSA) which consists of the cocentered orthogonal dipole triads (CODTs) to estimate two-dimensional direction-of-arrival (2D DOA) and polarization parameters. The degrees of freedom (DOFs) have been extended due to the co-prime structure, so that the more signals can be detected and the estimation accuracy is improved. In order to reduce the computation complexity, we construct a new cross-covariance matrix based on the CODTs, which converts the two-dimensional DOA estimation into two independent one-dimensional DOA estimations. Then, the spatial smoothing-based multiple signal classification algorithm(MUSIC) and the sparse representation-based method are applied to estimate 2D DOA with only one-dimensional (1D) peak searching and 1D dictionary, respectively. Finally, the polarization parameters are estimated by using the cross-covariance matrix between components of electric field vector. Compared with previous PSA-based algorithms, the proposed algorithm based on PCP-PSA can solve the underdetermined 2D DOA and polarization parameters estimation problem and has better estimation accuracy. Theoretical analyses and simulation results verify the effectiveness of the proposed methods in terms of computational complexity and estimation accuracy.

An improved peak clustering algorithm for comprehensive two-dimensional liquid chromatography data analysis

In this work, an improved algorithm was developed for two-dimensional (2D) peak detection in complex two-dimensional liquid chromatography (LC×LC) data sets. In the first step, conventional one-dimensional peak detection was performed. In the second step, retention time, bidirectional overlap and unimodality criteria were applied to decide which of the individual peaks should be merged. To improve the peak detection with LC×LC analysis using shifting second dimension (2D) gradients, the variable thresholds, which permitted different thresholds for candidate peaks at different first dimension (1D) retention times, were employed for examination of the 2D retention time differences. Furthermore, the bidirectional overlap criterion performed at specified height was recommended to improve detection for tailing peaks. The developed algorithm was further tested on data sets from different LC×LC analyses of a complex peptide mixture, and then quantitatively evaluated by comparison between the results by the algorithm and mass analysis. Evidently improved performance with an accuracy rate over 60% was obtained by the algorithm, even for peak detection with LC×LC analysis under relatively low 1D sampling frequency or shifting 2D gradients. This would help to improve LC×LC quantitative analysis and performance assessment.

Near Optimal Timing and Frequency Offset Estimation for 5G Integrated LEO Satellite Communication System

The integration of satellite and terrestrial 5G networks aims to provide ubiquitous coverage, improve service reliability, and enable the network scalability. However, the inherent characteristics of satellite channels bring challenges on the air interface design of integrated terrestrial-satellite networks. For example, for low earth orbits (LEO) mobile satellite communication (SatCom) system, it is unclear so far whether the 5G new radio (5G-NR) synchronization signals could meet the requirement of timing and frequency offset estimation in the presence of large Doppler shifts. In this paper, we investigate time and frequency synchronization for the downlink transmission of 5G-NR signals over LEO satellite channels. Starting from the maximum log-likelihood criterion for timing offset estimation given the observation of the received primary synchronization signals (PSS), we derive an upper bound of the objective function for simplicity. With a priori information that the maximum Doppler shift of LEO satellite-ground link is within a specific range, we construct the local synchronization sequence via using the modulated discrete prolate spheroidal sequences (DPSS) vectors. Then the timing offset estimation can be recast into a one-dimensional peak search problem. Moreover, the cyclic prefix (CP) structure of orthogonal frequency division multiplexing (OFDM) can be utilized to improve the estimation performance further. Once the timing and frequency offset are captured in the above initial synchronization phase, the tracking synchronization can be much simplified as the variation of both the timing and frequency offset is very small between two adjacent synchronization blocks. Simulation results show that by using the proposed algorithms, the 5G-NR signals can achieve near optimal downlink time and frequency synchronization in typical LEO SatCom systems.

Radial velocity estimation of moving target based on maximum likelihood estimation

For conventional multichannel synthetic aperture radar (SAR) systems, the pulse repetition frequency is greater than the azimuth Doppler bandwidth. Therefore, each receive channel can obtain unambiguous SAR image and the moving target usually overlaps with no more than one clutter. However, for high-resolution wide-swath (HRWS) SAR systems, the PRF is usually much less than the Doppler bandwidth and thus the moving target may overlap with quite a few clutters, which will severely affect the estimation of the radial velocity of the moving target. A novel radial velocity estimation method based on maximum likelihood estimation (MLE) for HRWS SAR systems is presented. Even if the moving target overlaps with quite a few clutters, the proposed MLE method can still effectively estimate the radial velocity. In order to reduce the computational load, the proposed method transforms the multi-dimensional spectral peak searching of MLE into one-dimensional peak searching and reduces the times of matrix inversion by a block matrix method. Theoretical analysis and experiments demonstrate the feasibility of the proposed method.

Estimation of DOA and polarization with COLD sensors based on quaternion model

The quaternion multiple signal classification (Q-MUSIC) algorithm generally requires four-dimensional spectral peak search to estimate the direction of arrival (DOA) and polarization parameters, which would result in the huge computation burden. A dimension reduction Q-MUSIC algorithm (DRQ-MUSIC) based on L-shaped array is presented to reduce the computational complexity in this paper. The proposed algorithm divides the steering vector into three parts, and estimates each part separately, thus DOA and polarization parameters can be estimated only by N times one-dimensional spectral peak search, where N denotes the sources number. Besides, pair match is not required. Finally, simulation examples demonstrate the effectiveness and feasibility of the proposed algorithm.

Inter-ribbon tunneling in graphene: An atomistic Bardeen approach

A weakly coupled system of two crossed graphene nanoribbons exhibits direct tunneling due to the overlap of the wavefunctions of both ribbons. We apply the Bardeen transfer Hamiltonian formalism, using atomistic band structure calculations to account for the effect of the atomic structure on the tunneling process. The strong quantum-size confinement of the nanoribbons is mirrored by the one-dimensional character of the electronic structure, resulting in properties that differ significantly from the case of inter-layer tunneling, where tunneling occurs between bulk two-dimensional graphene sheets. The current-voltage characteristics of the inter-ribbon tunneling structures exhibit resonance, as well as stepwise increases in current. Both features are caused by the energetic alignment of one-dimensional peaks in the density-of-states of the ribbons. Resonant tunneling occurs if the sign of the curvature of the coupled energy bands is equal, whereas a step-like increase in the current occurs if the signs are opposite. Changing the doping modulates the onset-voltage of the effects as well as their magnitude. Doping through electrostatic gating makes these structures promising for application towards steep slope switching devices. Using the atomistic empirical pseudopotentials based Bardeen transfer Hamiltonian method, inter-ribbon tunneling can be studied for the whole range of two-dimensional materials, such as transition metal dichalcogenides. The effects of resonance and of step-like increases in the current we observe in graphene ribbons are also expected in ribbons made from these alternative two-dimensional materials, because these effects are manifestations of the one-dimensional character of the density-of-states.

An online peak extraction algorithm for ion mobility spectrometry data

Ion mobility (IM) spectrometry (IMS), coupled with multi-capillary columns (MCCs), has been gaining importance for biotechnological and medical applications because of its ability to detect and quantify volatile organic compounds (VOC) at low concentrations in the air or in exhaled breath at ambient pressure and temperature. Ongoing miniaturization of spectrometers creates the need for reliable data analysis on-the-fly in small embedded low-power devices. We present the first fully automated online peak extraction method for MCC/IMS measurements consisting of several thousand individual spectra. Each individual spectrum is processed as it arrives, removing the need to store the measurement before starting the analysis, as is currently the state of the art. Thus the analysis device can be an inexpensive low-power system such as the Raspberry Pi.The key idea is to extract one-dimensional peak models (with four parameters) from each spectrum and then merge these into peak chains and finally two-dimensional peak models. We describe the different algorithmic steps in detail and evaluate the online method against state-of-the-art peak extraction methods.

Integration of neutron time-of-flight single-crystal Bragg peaks in reciprocal space

The intensity of single-crystal Bragg peaks obtained by mapping neutron time-of-flight event data into reciprocal space and integrating in various ways is compared. These methods include spherical integration with a fixed radius, ellipsoid fitting and integration of the peak intensity, and one-dimensional peak profile fitting. In comparison to intensities obtained by integrating in real detector histogram space, the data integrated in reciprocal space result in better agreement factors and more accurate atomic parameters. Furthermore, structure refinement using integrated intensities from one-dimensional profile fitting is demonstrated to be more accurate than simple peak-minus-background integration.

Novel angle estimation for bistatic MIMO radar using an improved MUSIC

In this article, we study the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar and propose an improved multiple signal classification (MUSIC) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation. The proposed algorithm obtains initial estimations of angles obtained from the signal subspace and uses the local one-dimensional peak searches to achieve the joint estimations of DOD and DOA. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm, and is almost the same as that of two-dimensional MUSIC. Furthermore, the proposed algorithm can be suitable for irregular array geometry, obtain automatically paired DOD and DOA estimations, and avoid two-dimensional peak searching. The simulation results verify the effectiveness and improvement of the algorithm.

Reduced-Dimension MUSIC for Angle and Array Gain-Phase Error Estimation in Bistatic MIMO Radar

In this letter, the problem of joint angle and array gain-phase error estimation for bistatic multiple-input multiple- output (MIMO) radar is investigated, and an algorithm for joint estimation with the characteristics of multiple signal classification (MUSIC) is proposed. Through reduced-dimension transform, the angles can be obtained via two one-dimensional peak searches, and the array gain-phase error can be estimated by utilizing the estimated angles. The proposed algorithm can achieve automatically paired estimations of the angles, and is suitable for non-uniform linear array. For the case of separately-located ca-librated sensors, the algorithm can also work well. Furthermore, it has better angle and array gain-phase error estimation performance than the ESPRIT-like algorithm. The simulation results verify the algorithmic effectiveness and robustness of our proposed algorithm.

Bayesian Approach for Peak Detection in Two-Dimensional Chromatography

A new method for peak detection in two-dimensional chromatography is presented. In a first step, the method starts with a conventional one-dimensional peak detection algorithm to detect modulated peaks. In a second step, a sophisticated algorithm is constructed to decide which of the individual one-dimensional peaks have been originated from the same compound and should then be arranged in a two-dimensional peak. The merging algorithm is based on Bayesian inference. The user sets prior information about certain parameters (e.g., second-dimension retention time variability, first-dimension band broadening, chromatographic noise). On the basis of these priors, the algorithm calculates the probability of myriads of peak arrangements (i.e., ways of merging one-dimensional peaks), finding which of them holds the highest value. Uncertainty in each parameter can be accounted by adapting conveniently its probability distribution function, which in turn may change the final decision of the most probable peak arrangement. It has been demonstrated that the Bayesian approach presented in this paper follows the chromatographers' intuition. The algorithm has been applied and tested with LC × LC and GC × GC data and takes around 1 min to process chromatograms with several thousands of peaks.

DOA Estimation Algorithm in Switch Antenna Array with a Single Cycle of Sampled Data

For DOA estimation of coherent signals in switch antenna array (SAA), a new fast algorithm is proposed. Instead of conventional sub-space algorithm’s covariance matrix, a Toeplitz matrix is constructed with a single cycle of sampled data. It is proved theoretically that the ranks of the Toeplitz matrix is equal to the number of signal sources and has no relations with the coherency of the signal source. Through eigenvalue decomposition, signal and noise subspace are obtained respectively, then DOA estimation can be done by one-dimensional spectral peak searching according to the MUSIC algorithm. The theoretical analysis and simulation results demonstrate validity and superiority of the novel algorithm.

Comprehensive Study on the Optimization of Online Two-Dimensional Liquid Chromatographic Systems Considering Losses in Theoretical Peak Capacity in First- and Second-Dimensions: A Pareto-Optimality Approach

A method to optimize different objectives (total analysis time, total peak capacity, and total dilution) has been applied to comprehensive two-dimensional liquid chromatography. The approach is based on Pareto-optimality, and it yields optimal parameters (column particle sizes, column diameters, and modulation times). Losses in the peak capacities in the first dimension (due to undersampling) and in the second dimension (due to high injection volumes) have been taken into account. The first effect (detection band broadening) reduces the original peak capacity by about a half, the second effect can reduce the total peak capacity by an additional half. Thus, the total loss in peak capacity may be 75% of its theoretical value. Analytical expressions to calculate these effects under gradient and isocratic conditions are derived. Of particular interest is the study of the optimal modulation times, which corresponded to between 2 and 3 two-dimensional runs per one-dimensional peak. The effects of using gradient or isocratic elution, conventional (40 MPa) or "ultra-high" (100 MPa) pressures, and focusing between the first and second dimensions were also studied. A trade-off between total peak capacity, total analysis time, and total dilution can be established.

Distinctions among Conifer Exudates by Proton Magnetic Resonance Spectroscopy

Proton nuclear magnetic resonance spectra have been recorded of exudates harvested from 12 species from the family Araucariaceae, 40 from the Cupressaceae, and one from the Podocarpaceae. These spectra were compared with the spectra previously recorded of 82 species from the Pinaceae. These four families together represent all major groups of extant, resin-bearing conifers. A common set of 10 COSY two-dimensional cross-peaks generally define samples from the Pinaceae, a different set of six peaks define the Araucariaceae, and yet a third set of 10 peaks define the Cupressaceae, with a few exceptions. It is important that proton spectra can distinguish the Araucariaceae and the Cupressaceae, since carbon-13 spectra do not. The one-dimensional peaks not only confirm these familial distinctions but also often characterize genus and species uniquely.

Departure from Gaussianity of the Cosmic Microwave Background Temperature Anisotropies in the Three‐YearWMAPData

We test the hypothesis that the temperature of the cosmic microwave background is consistent with a Gaussian random field defined on the celestial sphere, using de-biased internal linear combination (DILC) map produced from the 3-year WMAP data. We test the phases for spherical harmonic modes with l <= 10 (which should be the cleanest) for their uniformity, randomness, and correlation with those of the foreground templates. The phases themselves are consistent with a uniform distribution, but not for l <= 5, and the differences between phases are not consistent with uniformity. For l=3 and l=6, the phases of the CMB maps cross-correlate with the foregrounds, suggestion the presence of residual contamination in the DLC map even on these large scales. We also use a one-dimensional Fourier representation to assemble a_lm into the \Delta T_l(\phi) for each l mode, and test the positions of the resulting maxima and minima for consistency with uniformity randomness on the unit circle. The results show significant departures at the 0.5% level, with the one-dimensional peaks being concentrated around \phi=180 degs. This strongly significant alignment with the Galactic meridian, together with the cross-correlation of DILC phases with the foreground maps, strongly suggests that even the lowest spherical harmonic modes in the map are significantly contaminated with foreground radiation.