scholarly journals Mixed Far-Field and Near-Field Source Localization Algorithm via Sparse Subarrays

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Jiaqi Song ◽  
Haihong Tao ◽  
Jian Xie ◽  
Chenwei Sun
Keyword(s):  
Near Field ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Far Field ◽  
Localization Algorithm ◽  
Range Estimation ◽  
Field Source ◽  
Quarter Wavelength ◽  
Shift Invariance ◽  
Array Aperture

Based on a dual-size shift invariance sparse linear array, this paper presents a novel algorithm for the localization of mixed far-field and near-field sources. First, by constructing a cumulant matrix with only direction-of-arrival (DOA) information, the proposed algorithm decouples the DOA estimation from the range estimation. The cumulant-domain quarter-wavelength invariance yields unambiguous estimates of DOAs, which are then used as coarse references to disambiguate the phase ambiguities in fine estimates induced from the larger spatial invariance. Then, based on the estimated DOAs, another cumulant matrix is derived and decoupled to generate unambiguous and cyclically ambiguous estimates of range parameter. According to the coarse range estimation, the types of sources can be identified and the unambiguous fine range estimates of NF sources are obtained after disambiguation. Compared with some existing algorithms, the proposed algorithm enjoys extended array aperture and higher estimation accuracy. Simulation results are given to validate the performance of the proposed algorithm.

scholarly journals A Novel Sparse Array for Localization of Mixed Near-Field and Far-Field Sources

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yinsheng Wang ◽  
WeiJia Cui ◽  
Yuxi Du ◽  
Bin Ba ◽  
Fengtong Mei
Keyword(s):  
Degrees Of Freedom ◽  
Near Field ◽  
Parameters Estimation ◽  
Estimation Accuracy ◽  
Far Field ◽  
Computation Complexity ◽  
Field Source ◽  
One Dimensional ◽  
Range Parameter ◽  
Array Aperture

As we all know, nested array can obtain a larger array aperture and more degrees of freedom using fewer sensors. In this study, we not only designed an enhanced symmetric nested array (ESNA), which achieved more consecutive lags and more unique lags compared with a generalized nested array but also developed a special cumulant matrix, in the case of a given number of sensors, which can automatically generate the largest consecutive lags of the array. First, the direction-of-arrivals (DOAs) of mixed sources are estimated using the special cumulant matrix. Then, we can estimate the range of the near-field source in the mixed source using a one-dimensional spectral search through estimated DOAs, and in the mixed sources, the near-field and far-field sources are classified by bringing in the range parameter. The largest consecutive lags and composition method of ESNA are also given, under a given number of sensors.Our algorithm has moderate computation complexity, which provides a higher resolution and improves the parameters’ estimation accuracy. Numerical simulation results demonstrate that the proposed array showed an outstanding performance under estimation accuracy and resolution ability for both DOA and range estimation compared with existing arrays of the same physical array sensors.

Ambiguity-Function-Based Methods for Near-Field Source Localization

2012 ◽  
Vol 160 ◽  
pp. 395-399
Author(s):  
Xin Sun ◽  
Hong Jiang ◽  
Bo Wang
Keyword(s):  
Source Localization ◽  
Signal To Noise Ratio ◽  
Near Field ◽  
High Accuracy ◽  
Ambiguity Function ◽  
Far Field ◽  
Range Estimation ◽  
Signal To Noise ◽  
Field Source ◽  
Stationary Signals

In this paper, the AD-MUSIC method for far-field source localization is introduced to near-field, a two-dimensional MUSIC method based on ambiguity function distribution is proposed. Further, a novel AD-ROOT-MUSIC method is proposed for near-field source localization which constructes two matrices based on ambiguity function. They both have high accuracy and resolution for the bearing and range estimation of non-stationary signals in the near field, even when the signal-to-noise ratio (SNR) is low. The effectivity of the methods are validated by simulations.

Direction of Arrival Estimation Under Near-Field Interference Using Matrix Filter

2015 ◽  
Vol 23 (04) ◽  
pp. 1540007 ◽  
Author(s):  
Guolong Liang ◽  
Wenbin Zhao ◽  
Zhan Fan
Keyword(s):  
Near Field ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Direction Of Arrival Estimation ◽  
Far Field ◽  
Data Simulation ◽  
Estimation Algorithms ◽  
Simulation Results

Direction of arrival (DOA) estimation is of great interest due to its wide applications in sonar, radar and many other areas. However, the near-field interference is always presented in the received data, which may result in degradation of DOA estimation. An approach which can suppress the near-field interference and preserve the far-field signal desired by using a spatial matrix filter is proposed in this paper and some typical DOA estimation algorithms are adjusted to match the filtered data. Simulation results show that the approach can improve capability of DOA estimation under near-field inference efficiently.

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 Central DOA Estimation Method for Exponential-Type Coherent Distributed Source Based on Fourth-Order Cumulant

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hao Li ◽  
Weijia Cui ◽  
Bin Ba ◽  
Haiyun Xu ◽  
Yankui Zhang
Keyword(s):  
Fourth Order ◽  
Exponential Type ◽  
Complexity Analysis ◽  
Estimation Method ◽  
Doa Estimation ◽  
Estimation Accuracy ◽  
Distributed Source ◽  
Sparse Array ◽  
Fourth Order Cumulant ◽  
Array Aperture

The performance of direction-of-arrival (DOA) estimation for sparse arrays applied to the distributed source is worse than that applied to the point source model. In this paper, we introduce the coprime array with a large array aperture into the DOA estimation algorithm of the exponential-type coherent distributed source. In particular, we focus on the fourth-order cumulant (FOC) of the received signal which can provide more useful information when the signal is non-Gaussian than when it is Gaussian. The proposed algorithm extends the array aperture by combining the sparsity of array space domain with the fourth-order cumulant characteristics of signals, which improves the estimation accuracy and degree of freedom (DOF). Firstly, the signal-received model of the sparse array is established, and the fourth-order cumulant matrix of the received signal of the sparse array is calculated based on the characteristics of distributed sources, which extend the array aperture. Then, the virtual array is constructed by the sum aggregate of physical array elements, and the position set of its maximum continuous part array element is obtained. Finally, the center DOA estimation of the distributed source is realized by the subspace method. The accuracy and DOF of the proposed algorithm are higher than those of the distributed signal parameter estimator (DSPE) algorithm and least-squares estimation signal parameters via rotational invariance techniques (LS-ESPRIT) algorithm when the array elements are the same. Complexity analysis and numerical simulations are provided to demonstrate the superiority of the proposed method.

RADIATED ACOUSTIC PRESSURE FROM A MOVING, NONUNIFORMLY VIBRATING CYLINDER WITH TWO SPHERICAL ENDCAPS

1994 ◽  
Vol 02 (01) ◽  
pp. 71-82 ◽  
Author(s):  
ZHAOXI WANG ◽  
SEAN F. WU
Keyword(s):  
Near Field ◽  
Translational Motion ◽  
Normal Component ◽  
Forward Direction ◽  
Numerical Results ◽  
Surface Velocity ◽  
Reverse Direction ◽  
Far Field ◽  
Field Source ◽  
Sound Diffraction

This paper presents numerical results of radiated acoustic pressures from a moving, nonuniformly vibrating cylinder with two spherical endcaps, based on an extended Kirchhoff integral formulation. Specifically, we consider cases in which the normal component of the surface velocity is nonzero on a portion of the surface, and zero elsewhere. Numerical results demonstrate that the radiation patterns depend critically on the frequency and source dimensions. For a noncompact source, the strongest radiation may not necessarily stem from a vibrating surface, but rather from a nonvibrating surface due to the effect of sound diffraction. The more noncompact the source is, the larger the number of side lobes in the near field and the more concentrated these side lobes will be. In the far field, however, the side lobes become smeared and less distinguishable. In other words, the effect of sound diffraction is greatly reduced in the far field. Source translational motion induces sound radiation in the perpendicular direction and enhances the radiated acoustic field in general. Enhancement in the forward direction is much greater than in the reverse direction.

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