scholarly journals Joint DOA and Polarization Estimation with Two Parallel Sparse Dipole Arrays

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Xie ◽  
Ling Wang ◽  
Zhaolin Zhang

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.

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yan-kui Zhang ◽  
Hai-yun Xu ◽  
Da-ming Wang ◽  
Bin Ba ◽  
Si-yao Li

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.


Author(s):  
Jin Ding ◽  
Minglei Yang ◽  
Baixiao Chen ◽  
Xin Yuan

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.


2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hao Li ◽  
Weijia Cui ◽  
Bin Ba ◽  
Haiyun Xu ◽  
Yankui Zhang

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.


2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Zhi-Chao Sha ◽  
Zhang-Meng Liu ◽  
Zhi-Tao Huang ◽  
Yi-Yu Zhou

This paper addresses the problem of direction-of-arrival (DOA) estimation of coherent signals in the presence of unknown mutual coupling, and an autoregression (AR) model-based method is proposed. The effects of mutual coupling can be eliminated by the inherent mechanism of the proposed algorithm, so the DOAs can be accurately estimated without any calibration sources. After the mixing matrix is estimated by independent component analysis (ICA), several parameter equations are established upon the mixing matrix. Finally, all DOAs of coherent signals are estimated by solving these equations. Compared with traditional methods, the proposed method has higher angle resolution and estimation accuracy. Simulation results demonstrate the effectiveness of the algorithm.


Sensors ◽  
2015 ◽  
Vol 15 (12) ◽  
pp. 30856-30869 ◽  
Author(s):  
Yuexian Wang ◽  
Matthew Trinkle ◽  
Brian Ng

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Cai Wen ◽  
Yan Zhou ◽  
Mingliang Tao ◽  
Jianxin Wu ◽  
Jinye Peng

High-resolution direction of arrival (DOA) estimation is a critical issue for mainbeam multitarget tracking in ground-based or airborne early warning radar system. A beam-Doppler unitary ESPRIT (BD-UESPRIT) algorithm is proposed to deal with this problem. Firstly, multiple snapshots without spatial aperture loss are obtained by using the technique of time-smoothing. Then the conjugate centrosymmetric discrete Fourier transform (DFT) matrix is used to transform the extracted data into beam-Doppler domain. Finally, the rotational invariance property of the space-time beam is exploited to estimate DOA of the target. The DOA estimation accuracy is improved greatly because the proposed algorithm takes full advantage of temporal information of the signal. Furthermore, the computational complexity of the presented algorithm is reduced dramatically, because the degree of freedom after beam transformation is very small and most of the operations are implemented in real-number domain. Numerical examples are given to verify the effectiveness of the proposed algorithm.


2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Chen Gu ◽  
Hong Hong ◽  
Yusheng Li ◽  
Xiaohua Zhu ◽  
Jin He

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.


Author(s):  
Fei Zhang ◽  
Zijing Zhang ◽  
Aisuo Jin ◽  
Chuantang Ji ◽  
Yi Wang

AbstractAiming at the problem that traditional direction of arrival (DOA) estimation methods cannot handle multiple sources with high accuracy while increasing the degrees of freedom (DOF), a new method for 2-D DOA estimation based on coprime array MIMO radar (SA-MIMO-CA) is proposed. First of all, in order to ensure the accuracy of multi-source estimation when the number of elements is finite, a new coprime array model based on MIMO (MIMO-CA) is proposed. This method is based on a new MIMO array-based co-prime array model (MIMO-CA), which improves the accuracy of multi-source estimation when the number of array elements is limited, and obtains a larger array aperture with a smaller number of array elements, and improves the estimation accuracy of 2-D DOA. Finally, the effectiveness and reliability of the proposed SM-MIMO-CA method in improving the DOF of array and DOA accuracy are verified by experiments.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xia Li ◽  
Buhong Wang

By transmitting multiple independent waveforms at the transmit side and processing echoes of spatial targets at the receive side, Multiple Input Multiple Output (MIMO) radar enjoys virtual array aperture expansion and more degree of freedom (DOF), both of which favors the application of direction finding or estimation of direction of arrival (DOA). The expanded virtual aperture provides higher angular resolution which also promotes the precision of DOA estimation, and the extra DOF brought by waveform diversity can be leveraged to focus energy in certain spatial region for better direction-finding capacity. However, beamspace methods which match certain beampatterns suffer from deteriorated performance and complexity in implementation, and the advantage of virtual array aperture is limited by its virtual element redundancy. As an important performance indicator of DOA estimation, Cramer–Rao Bound (CRB) is closely connected to the array configuration of the system. To reduce the complexity of the system and improve CRB performance at the same time, in this paper, the virtual array of MIMO radar is designed directly by selecting outputs from matched filters at the receive side. For the sake of fair comparison, both scenarios with and without priori directions are considered to obtain optimized virtual array configuration, respectively. The original combinatorial problems are approximated by sequential convex approximations methods which produce solutions with efficiency. Numerical results demonstrate that the proposed method can provide thinned virtual arrays with excellent CRB performance.


Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4320 ◽  
Author(s):  
Ming-Yang Cao ◽  
Xingpeng Mao ◽  
Xiaozhuan Long ◽  
Lei Huang

This paper addresses the direction-of-arrival (DOA) estimation problem using a uniform rectangular array with electromagnetic vector-sensors in correlated/coherent signal environments. The polarization information is separated from the steering matrix to decorrelate the signals. By developing a tensorial structured received measurements of the array, we propose a tensor-based eigenvector DOA estimation method. Then we apply the forward-backward averaging to the tensor since it obeys the centro-Hermitian structure. In addition, a tensor-based polarization parameters estimation method is presented. The proposed algorithms are superior to the state-of-the-art algorithms in terms of estimation accuracy of coherent signals while only demand a modest computation burden comparing with the latter ones. Simulation results are given to demonstrate the effectiveness of the proposed methods under different scenarios.


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