The paper proposes a fast method for the multidimensional parameter estimation of a polarization-sensitive array. Compared with conventional methods (e.g., MUSIC algorithm), the proposed method applies an iterative ap...
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The paper proposes a fast method for the multidimensional parameter estimation of a polarization-sensitive array. Compared with conventional methods (e.g., MUSIC algorithm), the proposed method applies an iterative approach based on Newton's method to obtain joint estimation results instead of a spectral search and dimension reduction. It also extends the original Newton method to the 4D scale using the Hessian matrix. To reduce the complexity of establishing the aim function, Nystrom's method is applied to process the covariance matrix. A new threshold is also proposed to select the results, which can accomplish the parameter estimation with a small number of iterations while guaranteeing a high estimation accuracy. Finally, the proposed algorithm is analyzed in detail and the numerical simulations of various algorithms are compared to verify its effectiveness.
In this paper, we investigate the problem of blind joint multi-parameter estimation for polarization-sensitive coprime linear arrays (PS-CLAs). We propose a reduced-dimensional polynomial root finding approach, which ...
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In this paper, we investigate the problem of blind joint multi-parameter estimation for polarization-sensitive coprime linear arrays (PS-CLAs). We propose a reduced-dimensional polynomial root finding approach, which first utilizes the relation between the two subarrays to reconstruct the spectrum function and then converts three-dimensional (3D) total spectral search (TSS) to one-dimensional (1D) TSS. Furthermore, 1D polynomial root finding technique is employed to obtain the ambiguous direction of arrival (DOA) estimates, for further saving the computational cost. Finally, the true DOA estimates can be obtained based on the arrangements with coprime property, and subsequently the polarization parameters can be estimated through pairing. In addition, the matching error of false targets can be avoided due to the relation between the two subarrays. The proposed approach only requires about 0.01% computational complexity of the 1D TSS method to achieve the same estimation performance and behaves better in resolution. Simulations are provided to validate the superiority of the proposed approach.
To reduce the complexity of direction-of-arrival (DOA) algorithms in polarization-sensitive arrays and maintain high estimation accuracy while decreasing runtime, this paper proposes a channel compression model based ...
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To reduce the complexity of direction-of-arrival (DOA) algorithms in polarization-sensitive arrays and maintain high estimation accuracy while decreasing runtime, this paper proposes a channel compression model based on orthogonal dipole arrays. In addition, a DOA estimation algorithm using atomic norm minimization (ANM) is introduced for this model. This algorithm performs eigenvalue decomposition on the covariance matrix of the data received from the polarization-sensitive channel compressed array. A new observation vector is constructed for the ANM problem under the channel compression model using the obtained eigenvalues and eigenvectors. Subsequently, a Toeplitz matrix is constructed from the optimal solution of the semi- positive definite programming (SDP) problem. The Vandermonde decomposition of the Toeplitz matrix provides estimates of the signal DOA parameters. By combining the vectorization result of the covariance matrix and the least-squares calculation, the polarization auxiliary angle and polarization phase angle information of the incident source are also obtained. Simulation experiments compare the root-mean-squared error (RMSE) of each algorithm at different angular intervals and signal-to-noise ratios (SNR) to confirm the validity of estimating DOA and polarization parameters.
The representation of electromagnetic wave polarizations and co-polarizations of antenna elements has extensively been studied and documented. Various approaches to the description of polarization have been derived ac...
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The representation of electromagnetic wave polarizations and co-polarizations of antenna elements has extensively been studied and documented. Various approaches to the description of polarization have been derived across different applications, and these different definitions may lead to confusion and ambiguity. In addition, in a joint direction of arrival (DoA) and polarization estimation, the receiving antenna polarization in the maximum gain direction is usually equated to the one from any incoming wave direction, leading to unacceptable estimation errors. To this end, a direction-finding model is proposed in this article, which makes use of arbitrarily polarized antennas to explore spatial polarization characteristics. Specifically, the relationship between the co-polarization of a transmitting and receiving antenna and the polarization of radiated electromagnetic waves is derived from a unified Cartesian coordinate system. Subsequently, a definition of quantification for antenna polarization is proposed, which can represent the polarization in direction-finding solutions more naturally and intuitively. In consideration of rotation and spatial polarization characteristics of the receiving antenna, the proposed direction-finding model is thus developed with a unified polarization representation. Moreover, an application algorithm based on this model is formulated. The attractive features of the proposed model are verified by simulations and experiments.
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