Modified UCA-ESPRIT and modified UCA-ROOT-MUSIC for estimating DOA of coherent signals using one snapshot

Abstract

Direction of arrival (DOA) estimation algorithms is the method used to estimate the direction of arrival angle of several signals impinging on a sensor array, which plays an important role in array signal processing. The requirement for DOA estimation arises in different areas of signal processing applications including radar, sonar, and wireless communications. The uniform circular array estimation of signal parameters via rotational invariance techniques (UCA-ESPRIT) and the root multiple signal classification for uniform circular array (UCA-ROOT-MUSIC) algorithms were proposed to estimate the DOA of coherent signals using one single snapshot. First, the mode excitation method was used to transform the uniform circular array (UCA) in element space into a virtual uniform linear array (VULA) in mode space as explained in many papers. Then, the Hermitian Toeplitz matrix was reconstructed from the observed data vector as a decorrelated algorithm in order to rearrange the data and to extend the dimensionality of the noise space. Consequently, signal and noise spaces could be estimated more accurately. The proposed method did not need forward/backward spatial smoothing of the covariance matrix, resulting in reduced computational complexity. Simulation results verify that the proposed algorithm with one snapshot has a close performance to the conventional mode of spatial smoothing with 100 snapshots.