Abstract
This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank- BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method.
Highlights
Array signal processing is an important branch of the information acquisition and detection field, which has been studied and applied extensively in the academic and industrial communities for nearly half a century [1,2,3]
Uniqueness of block component decomposition (BCD) modeling for the electromagnetic vector sensor (EMVS) array: The rank-( L1, L2, ·) BCD descried in Equation (14) is essentially unique, if A and Ψ are of full column rank, N ≥ 3 and all elements of {Sk }kK=1 are characterized by jointly continuous probability density functions
As an example, when the snapshot is five, the detection probability of the proposed algorithm reaches to 97% and increased by about 31.1%, 15.4% and 7.8% compared with ESPRIT (74%), TM-multiple signal classification (MUSIC) (84%) and canonical polyadic decomposition (CPD)
Summary
Array signal processing is an important branch of the information acquisition and detection field, which has been studied and applied extensively in the academic and industrial communities for nearly half a century [1,2,3]. The existing tensor-decomposition-based parameter estimation methods for the EMVS array are mostly based on the CPD modeling Such a model has the advantage of uniqueness, but decomposition factors must be rank-1, which may not be satisfied in practice [32]. Since the BCD method possesses the blind estimation feature, it can solve such a problem properly This paper takes this as the research motivation to investigate the parameter estimation algorithm based on the BCD modeling for the EMVS array. The other sections of this paper are organized as follows: Section 2 describes the received signal model of the EMVS array and introduces the BCD method; Section 3 develops the algorithm based on rank-( L1 , L2 , ·) BCD for 2D AOA estimation; Section 4 presents numerical simulations for verifying the proposed algorithm and demonstrates the comparison with the existing methods; the last section concludes this paper
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