2-D DOA Estimation for Nested Conformal Arrays via Sparse Reconstruction

In this letter, we devise a cylindrical conformal array with nested subarray structures and propose a two-dimensional (2-D) direction-of-arrival (DOA) algorithm via sparse reconstruction. By vectorizing the cross-covariance matrix of two nested subarray outputs, the elevation and azimuth angles are firstly separated in the coarray signal model. Subsequently, the elevation angles are estimated via sparse signal reconstruction, and the azimuth angles are estimated by solving the least squares (LS) problem. Compared with the existing schemes for uniform conformal arrays, our algorithm exploits the coarray aperture of the nested subarrays, and hence can provide higher estimation accuracy. Moreover, it can achieve automatic pairing of the 2-D DOA estimates. Numerical results verify the superiority of the proposed algorithm in comparison with the existing schemes.