Abstract
Coprime array isAsparse array composed of two uniform linear arrays with different spacing. When the two subarrays are inAnon-coherent distributed configuration, the direction of arrival (DOA) method based on the covariance analysis of the complete coprime array is no longer effective. According to the essential attribute that the distance between the elements of two subarrays can eliminate the angle ambiguity, based on the mathematical derivation, Aspatial spectral product DOA estimation method for incoherent distributed coprime arrays is proposed. Firstly, the spatial spectrum of each subarray is calculated by using the snapshot data of each subarray, and then the DOA estimation is realized by multiplying the spatial spectrum of each subarray. The simulation results show that the estimation accuracy and angle resolution of the present method are better than those of the traditional ambiguity resolution methods, and the estimation performance is good in the mutual coupling and low SNR environment, with the good adaptability and stability. Moreover, by using the flexibility of distributed array, the matching error is effectively solved through the rotation angle.
Highlights
Coprime array is a sparse array composed of two uniform linear arrays with different spacing
When the two subarrays are in a non⁃coherent distributed configuration, the direction of arrival ( DOA) method based on the covariance analysis of the complete coprime array is no longer effective
The simulation results show that the estimation accuracy and angle resolution of the present method are better than those of the traditional ambiguity resolution methods, and the estimation performance is good in the mutual coupling and low SNR environment, with the good adaptability and stability
Summary
对值得到信源方向 θ 的最大似然函数。 LML( θ) =| det{ A( θ) R^ SAH( θ) + σ^ 2I} | (23) - lnf2 = ln( det{ R2} ) + tr{ R2-1R^ 2} (33) 仿真实验 3 算法的适应性与稳定性 图 7 和图 8 为不同阵元数、信噪比、快拍情况 下,似然乘积算法均方根误差性能。 信源入射角度 分别为 30°和 60°,进行 300 轮蒙特卡罗模拟。 图 7 为似然乘积算法的快拍数与 RMSE 性能的 关系,其中快拍数分别为 L = 100,200,300,可以看出 随快拍数的增加角度估计性能也在变好。 这是由于
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