Abstract:
This paper studies the problem of 2-D direction of arrival (DOA) estimation with polarization sensitive array (PSA), in which polarized vector sensor is consisted of spat...Show MoreMetadata
Abstract:
This paper studies the problem of 2-D direction of arrival (DOA) estimation with polarization sensitive array (PSA), in which polarized vector sensor is consisted of spatially spread crossed-dipole (SSCD). It is well known that crossed-dipole vector sensor can obtain all the polarization information including HH, HV, VH, and VV. Consequently, it is one of the most popularly polarized vector sensor. Unfortunately, in the existing works, it is difficult to effectively solve the problem of DOA estimation with SSCD array. Motivated by this, this paper presents a sparse rectangular SSCD-PSA to solve this problem. First, the ESPRIT algorithm is adopted to calculate the high accuracy but ambiguous direction cosine estimation. Second, the polarization information in the data covariance matrix is incorporated into incident source to form a block sparse signal model, and then, the block orthogonal matching pursuit is used to get a coarse reference direction cosine estimation. At last, a finally fine 2-D DOA estimation can be obtained by disambiguation process using the combination of high accuracy but ambiguous and coarse reference direction cosine estimations. The proposed algorithm obtains the 2-D DOA estimation under the lowest components polarized vector sensor and keeps the advantage of low mutual coupling. The simulation results prove the effectiveness and correctness of the proposed algorithm.
Published in: IEEE Sensors Journal ( Volume: 18, Issue: 12, 15 June 2018)