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In this paper, we investigate the problem of direction of arrival (DOA) and polarization estimation for non-Gaussian signal in polarization-sensitive augmented coprime array. Instead of the second-order cumulant statistics, the fourth-order cumulant statistics of the received signals are used for parameter estimation because they can detect more information of the non-Gaussian signal. First, polarization-sensitive augmented coprime array is designed, where each sensor element is equipped with a pair of orthogonal electric dipoles. Furthermore, a low-complexity reduced-dimensional Capon algorithm which uses the fourth-order cumulant of the received array signal is proposed for DOA and polarization estimation. Only one-dimensional peak search is required by reconstructing peak search function. Theoretical analysis has proven the effectiveness of the algorithm, and simulation results demonstrate that the proposed fourth-order cumulant reduced-dimensional Capon algorithm outperforms the other algorithms.

Direct position determination (DPD) of noncircular (NC) sources for multiple nested arrays (NA) is researched in this study. For noncircular sources, the dimension reduction method is used to decrease the computing complexity and remove the noncircular phase. Furthermore, nested array and noncircular sources extend spatial degree of freedom. Due to inferior stability and noise susceptibility of original algorithm, we propose SNR weighted subspace data fusion (W-SDF) algorithm. Each observation station places a nested array, spatial smoothing technology, and sum and difference co-array are used to deal with the nested array. Simulation results show that under nested array and noncircular sources, the proposed W-SDF algorithm has decreased the complexity of the algorithm and improved the location accuracy, degree of freedom, and resolution.

Direct position determination (DPD) for augmented coprime arrays is investigated in this paper. Augmented coprime array expands degree of freedom and array aperture and improves positioning accuracy. Because of poor stability and noise sensitivity of the subspace data fusion (SDF) method, we propose two weighted subspace data fusion (W-SDF) algorithms for direct position determination. Simulation results show that two W-SDF algorithms have a prominent promotion in positioning accuracy than SDF, Capon, and propagator method (PM) algorithm for augmented coprime arrays. SDF based on optimal weighting (OW-SDF) is slightly better than SDF based on SNR weighting (SW-SDF) in positioning accuracy. The performance for DPD of the W-SDF method with augmented coprime arrays is better than that of the W-SDF method with uniform arrays.

Direct position determination (DPD) of noncircular (NC) sources with multiple nested arrays (NA) is investigated in this paper. Noncircular sources are used to expand the dimension of the received signal matrix, so the number of identifiable information sources and the accuracy of direct position determination are improved. Furthermore, nested array increases spatial degree of freedom. In this paper, the high-dimensional search problem of noncircular sources is investigated. Therefore, we propose algorithm dimension reduction subspace data fusion (RD-SDF) to reduce complexity and increase positioning accuracy. Simulation results show that the proposed RD-SDF algorithm for multiple nested arrays with noncircular sources has improved positioning accuracy with higher spatial degree of freedom than SDF, Capon, and two-step algorithms with uniform linear array and circular sources (CS).