New DOA algorithm using subspace projection and synthetic spatial spectrum

In this paper, we propose a new direction of arrival (DOA) estimator for sensor-array processing. The estimator we propose is a modified weighted noise subspace of MUSIC algorithm (MWNSM). The algorithm is to solve the problem that the MUSIC algorithm has a strong depends on the signal-to-noise ratio (SNR) and snapshots. The new method reconstructs the spatial spectrum function with both noise subspace and signal subspace in this paper. The key idea is to apply the full information contained in covariance matrix and change the projection weights of steering vector on the noise and signal subspace by their revised eigenvalues, respectively. Comparing with the MUSIC algorithm, it does not increase any computational complexity either, and remarkably, it has the advantages of simultaneously reducing noise and keeping the high-resolution ability under low SNR and small sample sized scenarios. Computer simulation results shows that the proposed algorithm has a better performance than the classical DOA methods.