In this paper, a sparse array design problem for non-Gaussian signal direction of arrival (DOA) estimation is investigated. Compared with conventional second-order cumulant- (SOC-) based methods, fourth-order cumulant- (FOC-) based methods achieve improved DOA estimation performance by utilizing all information from received non-Gaussian sources. Considering the virtual sensor location of vectorized FOC-based methods can be calculated from the second order difference coarray of sum coarray (2-DCSC) of physical sensors, it is important to devise a sparse array design principle to obtain extended degree of freedom (DOF). Based on the properties of unfolded coprime linear array (UCLA), we formulate the sparse array design problem as a global postage-stamp problem (GPSP) and then present an array design method from GPSP perspective. Specifically, for vectorized FOC-based methods, we divide the process of obtaining physical sensor location into two steps; the first step is to obtain the two consecutive second order sum coarrays (2-SC), which can be modeled as GPSP, and the solutions to GPSP can also be utilized to determine the physical sensor location sets without interelement spacing coefficients. The second step is to adjust the physical sensor sets by multiplying the appropriate coprime coefficients, which is determined by the structure of UCLA. In addition, the 2-DCSC can be calculated from physical sensors directly, and the properties of UCLA are given to confirm the degree of freedom (DOF) of the proposed geometry. Simulation results validate the effectiveness and superiority of the proposed array geometry.

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Traditional polarization-sensitive sensors involve a triplet of spatially collocated, orthogonally oriented, and diversely polarized electric dipoles. However, this kind of sensor has the drawback of severe mutual coupling among the three dipoles due to the characteristic of collocation, as well as low radiation efficiency because of the short length of the dipoles. Based on this problem, in this study we designed a new array structure called a ‘triple coprime array (TCA)’, equipped with long electric dipoles to obtain higher radiation efficiency. In this structure, the dipoles within different subarrays have orthogonal polarization modes, leading to mutual coupling isolation. The dipole interval of the subarrays is enlarged by means of a pairwise coprime relationship, which further weakens the mutual coupling effect and extends the array aperture. Simultaneously, a stable direction-of-arrival (DOA) and polarization estimation method is proposed. DOA information is accurately refined from the three subarrays without ambiguity problems, with the triple coprime characteristic improving the estimation results. Subsequently, polarization estimates can be obtained using the reconstructed model matrix and the least squares method. Numerous theoretical analyses were conducted and extensive simulation results verified the advantages of the TCA structure in mutual coupling, along with the superiority of the proposed joint DOA and polarization estimation algorithm in terms of estimation accuracy.