A single triangular SS-EMVS aided high-accuracy DOA estimation using a multi-scale L-shaped sparse array

Abstract We propose a new array configuration composed of multi-scale scalar arrays and a single triangular spatially spread electromagnetic-vector-sensor (SS-EMVS) for high-accuracy two-dimensional (2D) direction-of-arrival (DOA) estimation. Two scalar arrays are placed along x-axis and y-axis, respectively, each array consists of two uniform linear arrays (ULAs), and these two ULAs have different inter-element spacings. In this manner, these two scalar arrays form a multi-scale L-shaped array. The two arms of this L-shaped scalar array are connected by a six-component SS-EMVS, which is composed of a spatially spread dipole-triad plus a spatially spread loop-triad. All the inter-element spacings in our proposed array can be larger than a half-wavelength of the incident source, thus to form a sparse array to mitigate the mutual coupling across antennas. In the proposed DOA estimation algorithm, we perform the vector-cross-product algorithm to the SS-EMVS to obtain a set of low-accuracy but unambiguous direction cosine estimation as a reference; we then impose estimation of signal parameters via rotation invariant technique (ESPRIT) algorithm to the two scalar arrays to get two sets of high-accuracy but cyclically ambiguous direction cosine estimations. Finally, the coarse estimation is used to disambiguate the fine but ambiguous estimations progressively and therefore a multiple-order disambiguation algorithm is developed. The proposed array enjoys the superiority of low redundancy and low mutual coupling. Moreover, the thresholds of the inter-sensor spacings utilized in the proposed array are also analyzed. Simulation results validate the performance of the proposed array geometry.

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Two-Dimensional DOA Estimation for Monostatic MIMO Radar with Electromagnetic Vector Received Sensors

International Journal of Antennas and Propagation ◽

10.1155/2016/2952539 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Guimei Zheng ◽

Jun Tang

Keyword(s):

Electromagnetic Field ◽

Estimation Method ◽

Estimation Algorithm ◽

Doa Estimation ◽

Field Vector ◽

Cross Product ◽

Mimo Radar ◽

Two Dimensional ◽

Array Configuration ◽

2D Doa Estimation

We study two-dimensional direction of arrival (2D-DOA) estimation problem of monostatic MIMO radar with the receiving array which consists of electromagnetic vector sensors (EMVSs). The proposed angle estimation algorithm can be applied to the arbitrary and unknown array configuration, which can be summarized as follows. Firstly, EMVSs in the receiver of a monostatic MIMO radar are used to measure all six electromagnetic-field components of an incident wavefield. The vector sensor array with the six unknown electromagnetic-field components is divided into six spatially identical subarrays. Secondly, ESPRIT is utilized to estimate the rotational invariant factors (RIFs). Parts of the RIFs are picked up to restore the source’s electromagnetic-field vector. Last, a vector cross product operation is performed between electric field and magnetic field to obtain the Pointing vector, which can offer the 2D-DOA estimation. Prior knowledge of array elements’ positions and angle searching procedure are not necessary for the proposed 2D-DOA estimation method. Simulation results prove the validity of the proposed method.

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Joint DOA and Polarization Estimation with Two Parallel Sparse Dipole Arrays

Mathematical Problems in Engineering ◽

10.1155/2018/5631714 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Jian Xie ◽

Ling Wang ◽

Zhaolin Zhang

Keyword(s):

Parameter Estimation ◽

Mutual Coupling ◽

Direction Cosine ◽

Doa Estimation ◽

Estimation Accuracy ◽

Invariance Property ◽

Array Configuration ◽

Vector Sensors ◽

Array Aperture ◽

Parallel Arrays

Electromagnetic vector sensors (EMVS) have attracted growing attention in recent years. However, the mutual coupling effects in practical EMVS arrays may seriously degrade the parameter estimation performance. In order to solve this problem, a novel array configuration consisting of two parallel sparse dipole arrays is proposed. Based on the spatially rotational invariance property between the two parallel arrays and the interdipole spacing inside each array, highly accurate but ambiguous direction-cosine estimates, coarse direction-of-arrival (DOA) estimates, and polarization parameter estimation can be obtained jointly. The coarse DOA estimates are then employed to disambiguate the phase ambiguities in the fine estimates. Compared with collocated EMVS, the proposed array overcomes the mutual coupling problem. Moreover, the DOA estimation accuracy is promoted due to the sparse array aperture extension. Simulation results demonstrate the effectiveness of the proposed algorithm.

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Thermos Array: Two-Dimensional Sparse Array with Reduced Mutual Coupling

International Journal of Antennas and Propagation ◽

10.1155/2018/3624514 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Lei Sun ◽

Minglei Yang ◽

Baixiao Chen

Keyword(s):

Closed Form ◽

Degrees Of Freedom ◽

Mutual Coupling ◽

Doa Estimation ◽

Two Dimensional ◽

Spatial Smoothing ◽

Planar Arrays ◽

Half Wavelength ◽

Planar Array ◽

Small Spacing

Sparse planar arrays, such as the billboard array, the open box array, and the two-dimensional nested array, have drawn lots of interest owing to their ability of two-dimensional angle estimation. Unfortunately, these arrays often suffer from mutual-coupling problems due to the large number of sensor pairs with small spacing d (usually equal to a half wavelength), which will degrade the performance of direction of arrival (DOA) estimation. Recently, the two-dimensional half-open box array and the hourglass array are proposed to reduce the mutual coupling. But both of them still have many sensor pairs with small spacing d, which implies that the reduction of mutual coupling is still limited. In this paper, we propose a new sparse planar array which has fewer number of sensor pairs with small spacing d. It is named as the thermos array because its shape seems like a thermos. Although the resulting difference coarray (DCA) of the thermos array is not hole-free, a large filled rectangular part in the DCA can be facilitated to perform spatial-smoothing-based DOA estimation. Moreover, it enjoys closed-form expressions for the sensor locations and the number of available degrees of freedom. Simulations show that the thermos array can achieve better DOA estimation performance than the hourglass array in the presence of mutual coupling, which indicates that our thermos array is more robust to the mutual-coupling array.

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2D-DOA Estimation for Cylindrical Array with Mutual Coupling

Mathematical Problems in Engineering ◽

10.1155/2014/716978 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Hao Feng ◽

Lutao Liu ◽

Biyang Wen

Keyword(s):

Mutual Coupling ◽

Estimation Algorithm ◽

Doa Estimation ◽

Coupling Matrix ◽

Estimation Algorithms ◽

Conformal Array ◽

Signal Parameters ◽

2D Doa Estimation ◽

Two Parameter ◽

Cylindrical Array

Most conventional direction-of-arrival (DOA) estimation algorithms are affected by the effect of mutual coupling, which make the performance of DOA estimation degrade. In this paper, a novel DOA estimation algorithm for conformal array in the presence of unknown mutual coupling is proposed. The special mutual coupling matrix (MCM) is applied to eliminate the effect of mutual coupling. With suitable array design, the decoupling between polarization parameter and angle information is accomplished. The two-demission DOA (2D-DOA) estimation is finally achieved based on estimation of signal parameters via rotational invariance techniques (ESPRIT). The proposed algorithm can be extended to conical conformal array as well. Two parameter pairing methods are illustrated for cylindrical and conical conformal array, respectively. The computer simulation verifies the effectiveness of the proposed algorithm.

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A FAST DOA ESTIMATION ALGORITHM FOR UNIFORM CIRCULAR ARRAYS IN THE PRESENCE OF UNKNOWN MUTUAL COUPLING

Progress In Electromagnetics Research C ◽

10.2528/pierc11042606 ◽

2011 ◽

Vol 21 ◽

pp. 257-271 ◽

Cited By ~ 5

Author(s):

Julan Xie ◽

Zi-Shu He ◽

Hui-Yong Li

Keyword(s):

Mutual Coupling ◽

Estimation Algorithm ◽

Doa Estimation ◽

Circular Arrays

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COPRIME ARRAY PARAMETERS OPTIMIZATION FOR DOA ESTIMATION

Iraqi Journal of Information & Communications Technology ◽

10.31987/ijict.4.2.131 ◽

2021 ◽

Vol 4 (2) ◽

pp. 23-32

Author(s):

Fatimah A. Salman ◽

Bayan M. Sabbar

Keyword(s):

Mutual Coupling ◽

Direction Of Arrival ◽

Doa Estimation ◽

Parameters Optimization ◽

Degree Of Freedom ◽

Direction Of Arrival Estimation ◽

Sparse Arrays ◽

Sparse Array ◽

Simulation Results ◽

Coprime Array

Sparse array such as the coprime array is one of the most preferable sparse arrays for direction of arrival estimation due to its properties, like simplicity, capability of resolving more sources than the number of elements and resistance to mutual coupling issue. In this paper, a new coprime array model is proposed to increase the number of degree of freedom (DOF) and improve the performance of coprime array. The new designed array can avoid the mutual coupling by minimizing the lag redundancy and expand the central lags in the virtual difference co-array. Thus, the propose structure can resolve more sources than the prototype coprime array using the same number of elements with improved direction of arrival estimation. Simulation results demonstrate that the proposed array model is more efficient than the others coprime array model.

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Highly Accurate Multi-Invariance ESPRIT for DOA Estimation with a Sparse Array

Mathematical Problems in Engineering ◽

10.1155/2019/5325817 ◽

2019 ◽

Vol 2019 ◽

pp. 1-7

Author(s):

Chen Gu ◽

Hong Hong ◽

Yusheng Li ◽

Xiaohua Zhu ◽

Jin He

Keyword(s):

Doa Estimation ◽

Invariance Property ◽

Two Dimensional ◽

Sparse Array ◽

Half Wavelength ◽

Vector Sensors ◽

Matrix Blocks ◽

Simulation Results ◽

Non Gaussian ◽

Array Geometry

This paper proposes a multi-invariance ESPRIT-based method for estimation of 2D direction (MIMED) of multiple non-Gaussian monochromatic signals using cumulants. In the MIMED, we consider an array geometry containing sparse L-shaped diversely polarized vector sensors plus an arbitrarily-placed single polarized scalar sensor. Firstly, we define a set of cumulant matrices to construct two matrix blocks with multi-invariance property. Then, we develop a multi-invariance ESPRIT-based algorithm with aperture extension using the defined matrix blocks to estimate two-dimensional directions of the signals. The MIMED can provide highly accurate and unambiguous direction estimates by extending the array element spacing beyond a half-wavelength. Finally, we present several simulation results to demonstrate the superiority of the MIMED.

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A Novel Designed Sparse Array for Noncircular Sources with High Degree of Freedom

Mathematical Problems in Engineering ◽

10.1155/2019/1264715 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Yan-kui Zhang ◽

Hai-yun Xu ◽

Da-ming Wang ◽

Bin Ba ◽

Si-yao Li

Keyword(s):

Design Method ◽

Doa Estimation ◽

Degree Of Freedom ◽

Estimation Accuracy ◽

Sparse Array ◽

Array Configuration ◽

Virtual Array ◽

Array Aperture ◽

Coprime Array ◽

High Degree

The existing coprime array is mainly applicable to circular sources, while the virtual array degree of freedom (DOF) for noncircular sources is enhanced limitedly. In order to perfect the array DOF and the direction of arrival (DOA) estimation accuracy, a high degree of freedom sparse array design method for noncircular sources is put forward. Firstly, the method takes the advantages of the characteristic of the noncircular sources to expand the array manifold and then explores and solves the location distribution of the physical array sensors on the basis of the virtual array model with the help of the searching approach. The array configuration can obtain the longest continuous virtual array. The comparisons between the proposed array configuration and the common array configurations are advanced. The simulation experiments show that the sparse array presented in this paper can effectively increase the continuous virtual array aperture of noncircular sources, improve the array DOF and DOA estimation accuracy, and achieve the purpose of better estimation of multiple DOAs in underdetermined conditions.

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