Near-field Sources Research Articles

A Novel Method Based on Oblique Projection Technology for Mixed Sources Estimation

Reducing the computational complexity of the near-field sources and far-field sources localization algorithms has been considered as a serious problem in the field of array signal processing. A novel algorithm caring for mixed sources location estimation based on oblique projection is proposed in this paper. The sources are estimated at two different stages and the sensor noise power is estimated and eliminated from the covariance which improve the accuracy of the estimation of mixed sources. Using the idea of compress, the range information of near-field sources is obtained by searching the partial area instead of the whole Fresnel area which can reduce the processing time. Compared with the traditional algorithms, the proposed algorithm has the lower computation complexity and has the ability to solve the two closed-spaced sources with high resolution and accuracy. The duplication of range estimation is also avoided. Finally, simulation results are provided to demonstrate the performance of the proposed method.

5D Parameter Estimation of Near-Field Sources Using Hybrid Evolutionary Computational Techniques

Hybrid evolutionary computational technique is developed to jointly estimate the amplitude, frequency, range, and 2D direction of arrival (elevation and azimuth angles) of near-field sources impinging on centrosymmetric cross array. Specifically, genetic algorithm is used as a global optimizer, whereas pattern search and interior point algorithms are employed as rapid local search optimizers. For this, a new multiobjective fitness function is constructed, which is the combination of mean square error and correlation between the normalized desired and estimated vectors. The performance of the proposed hybrid scheme is compared not only with the individual responses of genetic algorithm, interior point algorithm, and pattern search, but also with the existing traditional techniques. The proposed schemes produced fairly good results in terms of estimation accuracy, convergence rate, and robustness against noise. A large number of Monte-Carlo simulations are carried out to test out the validity and reliability of each scheme.

Near-field beamforming with augmentable non-uniform arrays for far-field interference suppression

This paper addresses the problem of adaptive near-field beamforming in the presence of many far-field interferers. Minimally redundant and, more generally, augmentable non-uniform arrays span larger array apertures and permit adaptive discrimination of more sources than sensors but require spatial-stationarity and increased snapshot support, which precludes their use for dynamic, near-field sources. In this paper, adaptive beamforming with augmentable non-uniform arrays is proposed which nulls relatively static far-field interference while enabling the detection of dynamic near-field sources. The use of an augmentable under-sampled array permits formation of a covariance matrix that can be used to implement reduced-rank dominant rejection of more interferers than sensors. Meanwhile, near-field beamforming in bearing and range is achieved using only the physical non-uniformly spaced sensor locations. An interference dominated environment is simulated to demonstrate the increase of array gain achieved over current techniques in the low snapshot support regime. [Work sponsored by ONR.]

Intensity-based approach to characterize near-field acoustic environments of space flight vehicles

An intensity-based measurement probe has been developed to measure the magnitude, directivity, and spectral content of near-field rocket source noise. An array of the intensity-based measurement probes was deployed in a static test firing of the GEM-60 at Alliant Techsystems in Promontory, UT, in 2012. The probes were positioned along the shear layer of the rocket motor plume to enable a comparison of the resultant source characterization obtained via sound power type measurement approaches to traditional acoustic measurement methodologies. The measurement results demonstrate that the intensity-based probes advance the measurement and characterization of the near-field acoustic environment of rockets. Moreover, intensity-based acoustic data provides an important role in formulating more realistic sound source models, improving acoustic load estimations, and aiding in the development of the next-generation space flight vehicles via improved measurements of noise near the rocket plume.

Second-Order Statistics-Based Multi-Parameter Estimation of Near-Field Acoustic Sources

In this paper, a new approach based on the second-order statistics (SOS) and acoustic vector sensor (AVS) array is proposed, for localization estimation of near-field acoustic narrowband sources. Firstly, we choose the centrosymmetric uniform linear-array as the AVS arrangement, and the array is consistent with the coordinate axis direction of the acoustic vector-sensor. This estimation method makes good use of the acquisition information from the AVS, such as one-dimensional sound pressure and three-dimensional particle velocity, and has shown preferable performance for the parameter estimation of direction-of-arrival (DOA) and range of target acoustic sources in the near field. The estimation algorithm expands the near-field array manifold of one single acoustic vector sensor to the acoustic vector-sensor’s uniform linear-array, and the near-field acoustic vector sensor linear array output model is deduced. The autocorrelation and cross-correlation function of the velocity field and the pressure field are used to construct the rotational invariance frame, which helps to extract the expected information. Consequently, the closed-form solutions of the incident source’s DOA and range are derived explicitly through the parameter pairing operation. The proposed method reduces the computational burden and has good spatial recognition ability and high resolution in the case of limited array elements. It also has better engineering application prospect. Eventually, the performance of the method is verified by Monte Carlo simulation experiments.

Multiple near‐field source localisation with uniform circular array

A subspace-based method is considered to deal with multiple near-field source localisation with a uniform circular array. The property of the centro-symmetric circular array configuration is employed and a matrix which is free of range is constructed. Then, the two-dimensional (2D)-MUSIC method is used to search the 2D angles after the range parameters are separated. After the 2D angles are estimated, a 1D-MUSIC method is used to estimate the corresponding ranges when the estimated 2D angles are substituted into the original form of the received data. It is shown that the proposed method can deal with the case of multiple near-field sources, but with lower computational complexity than that of the available 3D MUSIC method; moreover, the 3D parameters are automatically paired.

Coexistence of Near-Field and Far-Field Sources: the Angular Resolution Limit

Passive source localization is a well known inverse problem in which we convert the observed measurements into information about the direction of arrivals. In this paper we focus on the optimal resolution of such problem. More precisely, we propose in this contribution to derive and analyze the Angular Resolution Limit (ARL) for the scenario of mixed Near-Field (NF) and Far-Field (FF) Sources. This scenario is relevant to some realistic situations. We base our analysis on the Smith's equation which involves the Cramér-Rao Bound (CRB). This equation provides the theoretical ARL which is independent of a specific estimator. Our methodology is the following: first, we derive a closed-form expression of the CRB for the considered problem. Using these expressions, we can rewrite the Smith's equation as a 4-th order polynomial by assuming a small separation of the sources. Finally, we derive in closed-form the analytic ARL under or not the assumption of low noise variance. The obtained expression is compact and can provide useful qualitative informations on the behavior of the ARL.

Fast Maximum Likelihood Localization of Near-Field Sources

Conventional methods for locating near-field sources generally suffer performance degradation when the assumption of uniform spatial Gaussian noise does not hold. In this paper study the scenario of non-uniform spatial Gaussian noise. First we construct the near-field signal model based on planar sensor array and derive the maximum likelihood method for obtaining the azimuth and distance of sound sources, then we proposed two fast algorithms-stepwise-concentrated maximum likelihood method(SML) and approximate maximum likelihood method(AML) to reduce the high computational complexity of maximum likelihood localization method. Simulation results show that the two proposed methods outperform conventional maximum likelihood method, with lower computational complexity and less mean squared error of both azimuth estimation and distance estimation.

Rapidly Parameterized Consumer Use Modeling for High-Throughput Exposure Predictions

Background: High-throughput, typically in vitro, biological activity assays allow the ToxCast™ and Tox21 projects to compare the biological activity of chemicals with known in vivo toxicity to those with little or no in vivo data. Further in vitro assays characterize key aspects of pharmacokinetics and allow in vitro-in vivo extrapolation to predict human uptake (mg/kg/day) that might be sufficient to cause bioactivity in vivo. Aims: Without a similar capability to make quantitative, albeit uncertain, forecasts of exposure, the putative risk due to an arbitrary chemical cannot be rapidly evaluated. Methods: Using physico-chemical properties and provisional chemical use categories, most of the ~10,000 Tox21 chemicals have been evaluated with respect to exposure potential from near-field sources. A mapping of chemicals to products, and products to uses, has been used to categorize chemicals with respect to potential uses within the home. A Bayesian methodology is used to infer ranges of exposures consistent with biomarkers measured in urine samples and reported by the National Health and Nutrition Examination Survey (NHANES) in 2012. For each demographic group reported by NHANES we consider permutations of linear regression models, including as few as one and as many as all physico-chemical and use factors. Results: The linear regression provides a predictor, calibrated to the NHANES data, that can be applied to the remainder of the Tox21 list. The variance of this calibration serves as an empirical determination of uncertainty. These exposure predictions are then directly compared to the doses predicted to cause bioactivity for ~250 ToxCast chemicals. Conclusions: For chemicals with no other source of information, this approach allows prediction of confidence interval within which the average human exposure due to near field sources is likely. This abstract does not necessarily reflect U.S. EPA policy.

Mixed Near-Field and Far-Field Sources Localization Using the Uniform Linear Sensor Array

Based on the ESPRIT-like and polynomial rooting methods, a high-performance and low computational cost localization algorithm for the mixed near-field sources (NFS) and far-field sources (FFS) is proposed using the uniform linear sensor array. First, we combine the steering vectors of the two subarrays to eliminate the range parameters and then yield a new steering vector, which only contains direction-of-arrival (DOA) information. Second, based on the ESPRIT-like and polynomial rooting methods, the DOAs of all NFSs and FFSs are obtained from the new steering vector. Third, with the DOA estimates, the range parameters are estimated depending on the polynomial rooting method again; and further according to the number of the closest to the unit circle roots, we can determine the number of sources at the same DOA direction. Finally, based on the size of the range parameters, the types (NFS or FFS) of sources can be confirmed. In addition, the proposed algorithm does not require the high-order statistics or any 1- or 2-D search and thus has low computational cost. Meanwhile, it makes full use of the array aperture and obtains outstanding estimation performance for both the DOA and range parameters. Moreover, the proposed algorithm avoids parameter match procedure. Numerical experiments show the performance of the proposed algorithm in this paper.

Near‐field source localisation using a velocity sensor array

This study presents a new algorithm for near-field source localisation by using a uniform linear array consisting of velocity-sensor pairs (VSPs). Two schemes are used for range and direction of arrival (DOA) estimation in the proposed algorithm. The first one exploits the acoustic velocity vector field's two Cartesian components and the triangular location relationship among the near-field sources and the VSPs. The resulting range and DOA estimates are ambiguity-free, regardless of the inter-sensor spacing. Whereas the second scheme uses the so-called electric angles to determine the ranges and DOAs. Although the derived estimates may be ambiguous in the case of the inter-sensor spacing larger than a quarter wavelength, this ambiguity can be removed by using the estimates obtained in the first scheme. Therefore the proposed algorithm can offer high estimation accuracy by increasing inter-sensor spacing (because of array aperture extension). In addition, the proposed algorithm does not require multidimensional search, pairing parameters or high-order statistics, hence, has a low computational complexity.

Passive localization of 3-D near-field sources in coexisted multiplicative noise and additive noise

By exploiting favorable characteristics of a uniform cross-array, a passive localization algorithm of narrowband sources in the spherical coordinates (azimuth, elevation and range) is proposed. Based on the properly chosen sensor outputs, we compute the third-order cyclic moment matrices, and exploit a pre-calibration technique to eliminate multiplicative noise. Then, we construct a parallel factor (PARAFAC) model, and adopt trilinear alternating least squares regression (TALS) to estimate three-dimensional (3-D) near-field parameters. The investigated algorithm is efficient in the sense that it can eliminate multiplicative noise and additive noise, provide the improved estimation accuracy, as well as avoid the parameter-pairing procedure. Simulation results are carried out to demonstrate the performance of the proposed algorithm.

Low‐complexity estimation of signal parameters via rotational invariance techniques algorithm for mixed far‐field and near‐field cyclostationary sources localisation

In this study, the authors propose an efficient third-order cyclic moment-based estimation of signal parameters via rotational invariance techniques algorithm to cope with the mixed far-field and near-field cyclostationary sources localisation problem. The key point is that the auto-pairing parameters of near-field bearing and range is realised by estimating the unique non-singular matrix between the signal subspace and the matrix of direction vectors. This algorithm firstly constructs two special third-order cyclic moment matrices, in which the rotational factor is the function of the direction-of-arrival (DOA) and range of mixed far-field and near-field sources. By implementing the singular value decomposition and the high-resolution multiple signal classification spectral search, the authors estimate the azimuth DOAs for all the incoming sources. Then, the authors perform the estimation of the unique non-singular matrix between the signal subspace and the matrix of direction vectors. Finally, the range of near-field sources is determined from the obtained rotational factor. The proposed algorithm is computationally more efficient than the previous works, and it avoids pairing parameters. Computer simulations are carried out to demonstrate the performance of the proposed algorithm.

Source location based on independent doublet array

A single source location method based on a independent doublet array is proposed. It is considered that the source is located at the far-field of each doublet and the near-field of the array. The presented method realises direction of arrival estimation by an ESPRIT-like technique, and the range of the source by array geometry successively. It provides a simple and search-free estimation method for single near-field source location. Simulation results are presented that verify the effectiveness of the method.

BFGS quasi-Newton location algorithm using TDOAs and GROAs

With the emergence of location-based applications in various fields, the higher accuracy of positioning is demanded. By utilizing the time differences of arrival (TDOAs) and gain ratios of arrival (GROAs), an efficient algorithm for estimating the position is proposed, which exploits the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method to solve nonlinear equations at the source location under the additive measurement error. Although the accuracy of two-step weighted-least-square (WLS) method based on TDOAs and GROAs is very high, this method has a high computational complexity. While the proposed approach can achieve the same accuracy and bias with the lower computational complexity when the signal-to-noise ratio (SNR) is high, especially it can achieve better accuracy and smaller bias at a lower SNR. The proposed algorithm can be applied to the actual environment due to its real-time property and good robust performance. Simulation results show that with a good initial guess to begin with, the proposed estimator converges to the true solution and achieves the Cramer-Rao lower bound (CRLB) accuracy for both near-field and far-field sources.

Sparse recovery method for far-field and near-field sources localization using oblique projection

In this paper, we propose a novel source localization method to estimate parameters of arbitrary field sources, which may lie in near-field region or far-field region of array aperture. The proposed method primarily constructs two special spatial-temporal covariance matrixes which can avoid the array aperture loss, and then estimates the frequencies of signals to obtain the oblique projection matrixes. By using the oblique projection technique, the covariance matrixes can be transformed into several data matrixes which only contain single source information, respectively. At last, based on the sparse signal recovery method, these data matrixes are utilized to solve the source localization problem. Compared with the existing typical source localization algorithms, the proposed method improves the estimation accuracy, and provides higher angle resolution for closely spaced sources scenario. Simulation results are given to demonstrate the performance of the proposed algorithm.

Matrix Pencil 기법을 이용한 근거리 음원 위치 추정 기법

In this paper, near-field source localization algorithm is presented using Matrix Pencil in Uniform Linear Array(ULA). Based on the centrosymmetry of the ULA, the proposed algorithm decouples the steering vectors which allow for the bearing estimation using Matrix pencil. With estimated bearing, the range estimation of each source is consequently obtained by defining 1D MUSIC spectrum. Simulation results are presented to validate the performance of the proposed algorithm.

Robust Bayesian super-resolution approach via sparsity enforcing a priori for near-field aeroacoustic source imaging

Near-field aeroacoustic imaging has been the focus of great attentions of researchers and engineers in aeroacoustic source localization and power estimation for decades. Recently the deconvolution and regularization methods have greatly improved spatial resolution of the beamforming methods. But neither are they robust to background noises in the low Signal-to-Noise Ratio (SNR) situation, nor do they provide a wide dynamic range of power estimation.In this paper, we first propose an improved forward model of aeroacoustic power propagation, in which, we consider background noises and forward model uncertainty for the robustness. To solve the inverse problem, we then propose a robust Bayesian super-resolution approach via sparsity enforcing a priori. The sparse prior of source powers can be modeled by double exponential distribution, which can improve the spatial resolution and promote wide dynamic range of source powers. Both the hyperparameters and source powers can be alternatively estimated by the Bayesian inference approach based on the joint Maximum A Priori optimization. Finally our Bayesian approach is compared with some of the state-of-the-art methods on simulated, real and hybrid data. The main advantages of our approach are of robustness to noise, a wide dynamic range, super spatial resolution, and non-necessity for prior knowledge of the source number or SNR. It is feasible to apply it for aeroacoustic imaging with the 2D non-uniform microphone array in wind tunnel tests, especially for near-field monopole and extended source imaging.

Mixed-Order MUSIC Algorithm for Localization of Far-Field and Near-Field Sources

This letter presents a new mixed-order MUSIC algorithm for far-field and near-field sources localization using a sparse symmetric array. By exploiting the special array geometry, the proposed algorithm constructs a cumulant matrix to estimate the directions of arrival (DOAs) of both far-field and near-field sources using the conventional MUSIC method. With the estimated DOAs and the covariance matrix of the sparse array, the far-field and near-field sources are identified and the range parameters of near-field sources are also obtained by defining the range spectrum. Compared with the traditional algorithms, the proposed algorithm has moderate computation complexity, and provides higher resolution, and also improves the parameters estimation accuracy. Simulation results are provided to demonstrate the performance improvement of the proposed method.

Thin metamaterial Luneburg lens for surface waves

By suitably patterning a metasurface, the phase velocity of surface waves may be manipulated. Here, a low-loss, thin (1/14th of the free-space wavelength), omnidirectional Luneburg lens, based upon a Sievenpiper ``mushroom'' array [Sievenpiper et al., IEEE Trans. Microwave Theory Tech. 47, 2059 (1999)], is fabricated and characterized at microwave frequencies. Surface waves excited using a near-field point source on the perimeter of the lens, exit the opposite side of the lens as planar wave fronts. The electric field of the surface wave is mapped out experimentally and compared to numerical simulations.