Near-field Sources Research Articles

Symmetric Nested MIMO Architecture for Mixed Far-Field and Near-Field Source Localization

Symmetric Nested MIMO Architecture for Mixed Far-Field and Near-Field Source Localization

Penetration of a spherical vortex into turbulence

The penetration of a spherical vortex into turbulence is studied theoretically and experimentally. The characteristics of the vortex are first analysed from an integral perspective that reconciles the far-field dipolar flow with the near-field source flow. The influence of entrainment on the vortex drag force is elucidated, extending the Maxworthy (J. Fluid Mech., vol. 81, 1977, pp. 465–495) model to account for turbulent entrainment into the vortex movement and vortex penetration into an evolving turbulent field. The physics are explored numerically using a spherical vortex (initial radius $R_0$ , speed $U_{v0}$ ), characterised by a Reynolds number $Re_0(=2R_0U_{v0}/\nu$ , where $\nu$ is the kinematic viscosity) of 2000, moving into decaying homogeneous turbulence (root-mean-square $u_0$ , integral scale $L$ ) with turbulent intensity $I_t=u_0/U_{v0}$ . When the turbulence is absent ( $I_t=0$ ), a wake volume flux leads to a reduction of vortex impulse that causes the vortex to slow down. In the presence of turbulence ( $I_t> 0$ ), the loss of vortical material is enhanced and the vortex speed decreases until it is comparable to the local turbulent intensity and quickly fragments, penetrating a distance that scales as $I_t^{-1}$ . In the experimental study, a vortex ( $Re_0\sim 1490\unicode{x2013}5660$ ) propagating into a statistically steady, spatially varying turbulent field ( $I_{ve}=0.02$ to 0.98). The penetration distance is observed to scale with the inverse of the turbulent intensity. Incorporating the spatially and temporally varying turbulent fields into the integral model gives a good agreement with the predicted trend of the vortex penetration distance with turbulent intensity and insight into its dependence on the structure of the turbulence.

Recursive-RARE-based three-dimensional parameter estimation of near-field source considering amplitude attenuation

This paper addresses the issue for near-field (NF) localization considering amplitude attenuation, proposing a recursive rank-reduction (RARE) method for three-dimensional (3-D) parameter estimation of NF sources incident on a symmetrical cross array. The proposed method constructs several one-dimensional (1-D) spectral peak search estimators to obtain two-dimensional angle and range parameters. Initially, using the received data from symmetrical array elements in one axis, a 1-D spectral peak search estimator is constructed. The origins of two types of pseudo peaks within this estimator are analyzed, and then, corresponding pseudo peaks removal methods, namely the initial screening method and the recursive RARE method, are presented to obtain the estimate of the first angle parameter. Subsequently, the estimated results are fed into another 1-D spectral peak search estimator constructed from the original received data to obtain the range parameter. Finally, the same process is applied to the other axis to obtain the second angle and range parameters, followed by a parameter matching operation for 3-D parameters. Compared to existing NF source localization methods, the proposed method more effectively eliminates pseudo peaks, and demonstrates superior parameter estimation performance under conditions of small number of snapshots and low signal-to-noise ratio, as validated by several simulation results.

An High Efficiency Angle and Range Estimation Method for Three-Dimensional Near-Field Sources Based on Higher-Order Cumulants

An High Efficiency Angle and Range Estimation Method for Three-Dimensional Near-Field Sources Based on Higher-Order Cumulants

A 3-D Near-Field Source Localization Approach Based on the Combination of a Phase Interferometer, the Centroid Algorithm and the Perpendicular Foot Algorithm.

In this study, several 3-dimensional (3-D) parameter estimation and localization algorithms for wireless near-field (NF) sources are proposed employing the uniform circular array (UCA) structure. In the single-base-station case, the algebraic relation is demonstrated between the azimuth angle under the far-field (FF) assumption and the actual NF source firstly. Secondly, two groups of antenna pairs are selected with distances less than half the wavelength, which are called short baselines in the interferometer method. The foregoing short-baseline method is qualified to localize an NF source. In addition, a long-baseline method is also proposed with further research. Two groups of antenna pairs with distances greater than half the wavelength are selected as two long baselines. In the multiple-base-stations case, another two novel algorithms are also proposed. The first one is the centroid algorithm, which is based on the centroid calculation of three estimated source locations. And the second one is the perpendicular foot algorithm, which takes the perpendicular foot within three estimated source locations as the final positioning location. Simulation results illustrate that the proposed algorithms can achieve higher localization accuracy than the conventional 3-D Root MUSIC method. Moreover, the long-baseline method performs better than the short-baseline method. And it is also shown that the proposed perpendicular foot algorithm shows better performance than the proposed centroid algorithm.

Effect of rotation speed fluctuation on rotor noise generation: A numerical and experimental study

The practical operations of rotors for unmanned aircraft systems can undergo time-varying rotation speeds due to various uncertainty factors. This work investigates the aeroacoustic effect of the rotor’s rotation speed fluctuation using both numerical and experimental approaches. The measured real-time angular speed signal reveals that a hovering rotor experiences highly deterministic rotation speed variations in one revolution, which are closely related to the motor property. Delayed detached eddy simulations are performed, and the fluctuating rotation speed is realized by controlling the mesh displacement at each time step. The results suggest that significant additional tones are produced at the excitation frequency and neighbour frequencies, even though the amplitudes of the rotation speed fluctuations at the dominant frequencies are much smaller than the mean rotation speed. By comparing the full signal to individual harmonic components, it is found that the phase difference between each mode is unimportant. Therefore, the total aeroacoustic effect can be regarded as a linear superposition of different harmonic components. Aeroacoustic source analysis is also performed to isolate the contribution of various source types and correlate the far-field noise with the near-field source distribution. The results show that the extra tonal noise is mostly dominated by the loading noise, with a weaker contribution from the thickness noise. The agreement between the experiments and the simulations indicates that the rotation speed fluctuation is likely responsible for the generation of middle-frequency tonal noise at harmonics of the blade passing frequency.

Bridge the gap between simulated and real-world data in optical fiber mode decomposition for accuracy improvement: A deep learning-based co-learning framework with visual similarity-based matching

In the area of optical fiber mode decomposition (MD), data-driven deep-learning (DL) algorithms have achieved remarkable strides with unlimited theoretically synthetic data, but the differences between theoretical and real-world data in the DL context are rarely investigated. The two differences, namely the information bottleneck and the domain discrepancy, between the simulation and realistic domain remain significant obstacles that limit the practical deployment of DL-based MD approaches in real-world optical systems. The paper aims to mitigate their influence on the accuracy limitation and the accuracy degradation of DL-based MD. First, we present a DL-based co-learning framework for MD for the first time. With the co-learning process, the knowledge of the teacher model learned from rich input information sources (near-field, far-field, and phase-distribution optical images) is transferred to the student model with the only near-field input source, which breaks the information bottleneck by allowing the student model to learn more knowledge in a simulation context. Furthermore, to settle the domain discrepancy between ideal data and practical observation, we propose a visual similarity-based matching to assign real values of modal coefficients to the practical optical images whose ground truth values cannot be easily acquired, which enables the transfer learning from the synthetic data to the real-world data for accuracy enhancement. Simulated and experimental results show that the proposed co-learning framework with visual similarity-based matching has realized high precision and robustness in MD simulated and practical tasks. By bridging the gap between theoretical and practical data, our study offers novel perspectives on DL-based MD practice.

A Novel Modified Symmetric Nested Array for Mixed Far-Field and Near-Field Source Localization

A Novel Modified Symmetric Nested Array for Mixed Far-Field and Near-Field Source Localization

Near-field DOA estimation oriented sparse array design via symmetric augmentation of three ULAs

A symmetric sparse array, via symmetric augmentation of three (SAT) uniform linear subarrays, has been designed for direction of arrival (DOA) estimation of uncorrelated near-field or coexisted near-field and far-field narrowband source signals. With an explicit design of the subarray structures and positions, this SAT array 1) involves only two closely spaced antenna pairs (with quarter-wavelength spacing); 2) has a large uniform degree of freedom (uDOF) and difference co-array; 3) can have either even or odd number of antennas; and 4) has closed form expressions for antenna positions, uDOF and weight functions. Simulation results show that the SAT array is superior to the current symmetric sparse arrays in both antenna mutual coupling and consecutive virtual aperture.

Enantioselective Surface-Enhanced Raman Scattering by Chiral Au Nanocrystals with Finely Modulated Chiral Fields and Internal Standards.

The chiral discrimination of enantiomers is crucial for drug screening and agricultural production. Surface-enhanced Raman scattering (SERS) is proposed for discriminating enantiomers benefiting from chiral plasmonic materials. However, the mechanism of enantioselective SERS is unclear, and fluctuating SERS intensities may result in errors. Herein, this work demonstrates a reliable SERS substrate using chiral Au nanocrystals with finely modulated chiral fields and internal standards. Chiral electromagnetic fields are enhanced after modulation, which is conducive to increasing the difference in the enantiomeric SERS intensity, as evidenced by the experimental and simulation results. Furthermore, the SERS stability is improved by the corrective effect of the internal standards, and the relative standard deviation is significantly reduced. Using finely modulated chiral fields and internal standards, L- and D-phenylalanine exhibit a stable six times difference in SERS ratio. Theoretical simulations reveal that linearly polarized light can also excite the chiral fields of chiral Au nanocrystals, indicating non-chiral far-field light is converted into chiral near-field sources by chiral Au nanocrystals. Thus, the mechanism of enantioselective SERS can be elucidated by the scattering difference of chiral molecules in chiral near fields. This study will pave the way for the development of enantioselective SERS and related chiroptical technologies.

Near-Field Source Localization and Beamforming in the Spherical Sector Harmonics Domain

Near-Field Source Localization and Beamforming in the Spherical Sector Harmonics Domain

Unified Near-Field and Far-Field TDOA Source Localization Without the Knowledge of Signal Propagation Speed

Unified Near-Field and Far-Field TDOA Source Localization Without the Knowledge of Signal Propagation Speed

Symmetric Double-Supplemented Nested Array for Passive Localization of Mixed Near-Field and Far-Field Sources

In mixed-field source localization, the physical properties of a sensor array, such as the degrees of freedom (DOFs), aperture, and coupling leakage, directly affect the accuracy of estimating the direction of arrival (DOA). Compared to conventional symmetric uniform linear arrays, symmetric non-uniform linear arrays (SNLAs) have a greater advantage in mixed-field source localization due to their larger aperture and higher DOF. However, current SNLAs require improvements in their physical properties through modifications to the array structure in order to achieve more accurate source localization estimates. Therefore, this study proposes a symmetric double-supplemented nested array (SDSNA), which translates nested subarrays based on symmetric nested arrays to increase the aperture and inserts two symmetric supplemented subarrays to fill the holes created by the translation. This method results in longer consecutive difference coarray lags and larger apertures. The SDSNA is compared to existing advanced SNLAs in terms of their physical properties and DOA estimation. The results show that, with the same number of sensors, the SDSNA has a higher DOF, a larger aperture, and smaller coupling, indicating the advantages of the SDSNA in terms of its physical properties. Under the same experimental conditions, the SDSNA has a lower root-mean-square error of source location, thus indicating better performance in terms of both DOA and distance estimation.

A 3-D spatial–temporal near-field parameter estimation method with two correlation operations

This paper proposes a narrowband near-field (NF) source localization algorithm based on two correlation operations. By utilizing the correlation of incident signal in the time and spatial domains, the algorithm achieves direction-of-arrival (DOA) with high-precision and low-complexity and range estimation under the virtual single snapshot. To do so, in the processing of NF source received signals, this paper first utilizes the symmetry of the cross-cross array and obtains a covariance matrix containing only azimuth and elevation information through two correlation operations. Since the covariance matrix has a standard two-level Toeplitz matrix form, the estimated parameters can be directly extracted from the noise-free covariance matrix without pairing using the two-level Vandermonde decomposition technique. Finally, the estimated value of the range is obtained using a one-dimensional (1-D) spectral peak search. Computer simulation results verify the superior performance of the proposed algorithm in terms of complexity and estimation accuracy.

Extension of Doak's momentum potential theory for multi-species and reacting flows.

This work extends Doak's momentum potential theory to multi-chemical-component and reactive, time-stationary fluctuating flows. Additional mixture-related components are found to be superimposed on the canonical vortical, acoustic, and thermal parts of momentum fluctuations and total fluctuating enthalpy. These extended relations are used to develop a time-averaged model that relates the acoustic power radiated to the far-field with clearly defined vortical, acoustic, thermal, and compositional near-field sources. The resulting model is designed to offer a more general and comprehensive way to describe the noise generated within combustion chambers.

A High Degree of Freedom Radiation Near-Field Source Localization Algorithm with Gain–Phase Error

The limitation of the number of estimable sources in the localization of radiation near-field sources with gain–phase error is examined in this paper. When only the reference element has no gain–phase error, a new method based on an accurate model is proposed to enhance the maximum number of estimable sources. Based on the location parameter details of the auxiliary source, the method first derives the gain–phase error estimate matrix. Second, the source steering vector including errors is estimated using the total least square estimating signal parameter via rotational invariance techniques (TLS-ESPRIT), and the time-shifted data matrix is built utilizing the space–time combination idea, thus increasing the degree of freedom of the array. Then, the source steering vector containing the error is modified by the error compensation matrix constructed according to the moment of gain–phase error estimation. Finally, the estimated values of the source position parameters are obtained by using the closed formula of the gain phase of the modified source steering vector and the source position parameters. The experimental results show that the maximum estimable source number of the proposed algorithm is significantly improved compared with the previous results when only the reference array element has no gain–phase error. When the array number is 5 and 9, the maximum estimable source number of the algorithm is 9 and 17, respectively.

Seismic response of non-structural components in multi-storey steel frames

This paper investigates the elastic and inelastic seismic response of non-structural components in multi-storey steel moment framed structures and derives predictive relationships for their displacements and spectral accelerations. Within 38 primary structural steel frames, non-structural components characterised by various periods and strength reduction factors, are modelled as single-degree-of-freedom systems which are fixed to individual floors. The primary structures are three, five, and seven-storey steel moment-resisting frames, designed according to the provisions of Eurocode 8. Detailed nonlinear time history analyses are conducted, employing a large set of 100 ground motion records from both far-field and near-field sources. These records are scaled to two distinct levels to simulate the response of primary structures in both elastic and inelastic states. The influence of the ground motion type and the inelasticity level in the non-structural components is examined in detail. The sensitivity to strain hardening and viscous damping considerations is also assessed and discussed. Based on the results, representative relationships for predicting the inelastic displacement ratios are proposed. In addition, various provisions stipulated in European design guidance for determining the spectral accelerations are critically evaluated and improvements are suggested with due consideration for the inelasticity of both the non-structural components and the primary structures.

Method and practice of microphone array speech source localization based on sound propagation modeling

Abstract This paper realizes the speech source localization for microphone arrays based on the sound propagation model. According to the actual environment and location of the sound source, this paper divides the sound source into far-field source and near-field source and constructs the far-field sound model and near-field sound model applicable to the microphone array. The TDOA time-delayed localization algorithm is employed to locate the voice source of the microphone array by judging the sound far and near the field. In the localization test, this paper selects microphones to form an array according to the actual needs and preprocesses the sound signal data required for practice. The preprocessing data and sound source localization practice prove that the microphone array speech source localization algorithm used in this paper can effectively estimate the actual position of the sound source, and the absolute error between its estimated sound source position and the actual sound source position is only about 0.3m.

Joint Estimation of DOA and Range for Near-Field Sources in the Presence of Far-Field Sources and Alpha-Stable Noise

Joint Estimation of DOA and Range for Near-Field Sources in the Presence of Far-Field Sources and Alpha-Stable Noise

Joint 3D coordinate and wave-speed estimation with nonuniform planar array: Multi-leak localization in gas pipe buried in sandy soil

The acoustic-based methods enable remote detection of gas pipeline leaks and provide the leak area. However, accurate localization of buried leaks within the leak area requires further investigation. In this scenario, the unknown wave speed in soils and the computational complexity associated with three-dimensional (3D) localization in underground spaces pose challenges. Therefore, a joint estimation method based on a specially-designed nonuniform planar array is proposed to determine both the leak position and wave-speed. Specifically, a small-aperture uniform subarray is embedded into the large-aperture nonuniform array. By utilizing the small-aperture subarray, we can solve for the relationship between wave-speed and direction of arrival (DOA) of far-field waves. Subsequently, two-dimensional spectrum estimation is performed using the large-aperture array to obtain estimates for both wave-speed and near-field source distance. Finally, without resorting to 3D spectrum estimation, the 3D coordinates of the leak are determined. Experimental results conducted on buried pipes demonstrate that the proposed method effectively works across three soil types at varying burial depths. Notably high accuracy is achieved using a large-aperture array expended from the uniform L-shaped array with RMSE less than 0.1 m at SNR of 15 dB. Both experimental validations and simulations confirm that the novel approach can be successfully applied in various scenarios.