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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.

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While the coprime array still suffers from performance degradation due to the mutual coupling dominated by the interleaved subarrays, we propose an array switching strategy for coprime linear array (CLA) by utilizing the large inter-element spacings of the subarrays to mitigate the mutual coupling. Specifically, we first collect the signals by separately activating the two subarrays, where the severe mutual coupling effect is significantly reduced. As a result, well-performed initial direction of arrival (DOA) estimates can be achieved. Subsequently, we establish a quadratic optimization problem by reconstructing the contaminated steering vector of the total CLA elaborately to calculate the mutual coupling coefficients with the initial DOA estimates. Finally, we can obtain refined DOA estimates by an iteration procedure based on the estimated mutual coupling matrix. In addition, numerical simulations are provided to demonstrate the merits of the proposed scheme.