A fast algorithm for direction of arrival estimation in multipath environments

A new spectral direction of arrival (DOA) estimation algorithm is proposed that can rapidly estimate the DOA of non-coherent as well as coherent incident signals. As such the algorithm is effective for DOA estimation in multi-path environments. The proposed method constructs a data model based on a Hermitian Toeplitz matrix whose rank is related to the DOA of incoming signals and is not affected if the incoming sources are highly correlated. The data is rearranged in such a way that extends the dimensionality of the noise space. Consequently, the signal and noise spaces can be estimated more accurately. The proposed method has several advantages over the well-known classical subspace algorithms such as MUSIC and ESPRIT, as well as the Matrix Pencil (MP) method. In particular, the proposed method is suitable for real-time applications since it does not require multiple snapshots in order to estimate the DOA's. Moreover, no forward/backward spatial smoothing of the covariance matrix is needed, resulting in reduced computational complexity. Finally, the proposed method can estimate the DOA of coherent sources. The simulation results verify that the proposed method outperforms the MUSIC, ESPRIT and Matrix Pencil algorithms.