LAUSR

In this paper, two noniterative direction-of-arrival (DOA) estimation algorithms of noncircular signals in nonuniform noise environment are proposed. Different from the mainstream nonuniform iterative algorithm, the algorithms we proposed in this paper could attain DOA estimation effectively in nonuniform noise environment without iterative and convex optimization processing. In the direct removal of nonuniform noise (DRONN) method, the noise subspace is estimated by using special processing of the array output covariance matrix, moreover, it does not require to estimate the noise covariance matrix. On the other hand, the piecewise estimation of nonuniform noise (PEONN) method first estimates the noise covariance matrix, and the noise subspace used in this process is estimated by using the DRONN method, then the generalized eigendecomposition (GED) is used to estimate the noise covariance matrix. The above two proposed methods are able to suppress the interference of nonuniform noise effectively, and accurately estimate DOA without iterative processing. In addition, the two proposed methods use the reduced-dimensional noncircular multiple signal classification (RD-NC-MUSIC) algorithm to estimate DOA without complex two-dimensional spatial search, and they can effectively reduce the computational complexity. The effectiveness of the two proposed methods are proved via the simulation results.