Abstract
Noncircular signals are widely used in the area of radar, sonar, and wireless communication array systems, which can offer more accurate estimates and detect more sources. In this paper, the noncircular signals are employed to improve source localization accuracy and identifiability. Firstly, an extended real-valued covariance matrix is constructed to transform complex-valued computation into real-valued computation. Based on the property of noncircular signals and symmetric uniform linear array (SULA) which consist of dual-polarization sensors, the array steering vectors can be separated into the source position parameters and the nuisance parameter. Therefore, the rank reduction (RARE) estimators are adopted to estimate the source localization parameters in sequence. By utilizing polarization information of sources and real-valued computation, the maximum number of resolvable sources, estimation accuracy, and resolution can be improved. Numerical simulations demonstrate that the proposed method outperforms the existing methods in both resolution and estimation accuracy.
Highlights
Passive source localization is a key problem in array signal processing for applications such as radar, sonar, microphone arrays, and communication [1]
Lee et al proposed a covariance approximation method (CA) [6]. e method reconstructed the elements of the NF covariance matrix, so that the NF source was converted into a virtual FF source, and the traditional FF direction finding methods could apply to the DOA estimation of FF sources, avoiding multidimensional search
We suppose that K independent NF noncircular signals impinge upon a symmetric uniform linear array (SULA) as shown in Figure 1. e array is composed of N 2M + 1 dual-polarization sensors which is placed along the y-axis, and its sensors position is [− M d, . . . , 0, . . . , M d], where d is the interelement spacing
Summary
Passive source localization is a key problem in array signal processing for applications such as radar, sonar, microphone arrays, and communication [1]. Based on the symmetric sparse linear array with dual-polarization sensors, Tao et al proposed the Fresnel-region rank reduction (FR-RARA) algorithm [17] that enhanced array aperture and only required second-order statistics. He et al presented a NF localization of partially polarization sources with a cross-dipole array [18]. En, based on the noncircularity of signals and the property of symmetric uniform linear array (SULA), the array steering vector could be decoupled as the product of three real-valued matrixes including DOA, range, and other nuisance parameters, respectively. R(·), I(·), and det(·) symbolize the real part operator, the imaginary part operator, and the determinant of a matrix
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