Direction of arrival estimation based on temporal and spatial processing using a direct data domain (D³) approach

The purpose of this paper is to estimate the direction of arrival (DOA) of the signal of interest (SOI) in the presence of both coherent and noncoherent interferences and multipath components utilizing a combined temporal and spatial processing technique based on a direct data domain approach. The concept of cyclostationarity, which deals with the temporal information of the SOI, is used to extract signals having the same cycle frequency and null out the co-channel interferences and additive noise. Hence, the signal detection capability can be significantly increased over conventional filtering when the length of the data record is limited. The main contribution of the paper is that by combining temporal and spatial processing based on a direct data domain approach one can handle number of signals along with their various coherent and noncoherent multipaths and interferences which can exceed the number of antenna elements. Hence, this methodology may be advantageous over conventional spatial processing when the number of degrees of freedom can never exceed the number of antenna elements in the array. However, the number of multipaths and interferers at the same cycle frequency has to be less than approximately 66% of the antenna elements. Since we do not form a covariance matrix of the data, this method is quite suitable for short data lengths or when the environment is quite dynamic. Hence, in the proposed algorithm, while the estimation of the cyclic array covariance matrix is avoided, we develop a new matrix form using extremely short data samples. As a result, the computational load in the proposed approach is relatively reduced and the robustness of the estimation of SOI is significantly improved when the number of available snapshots is extremely limited. Numerical results are presented to illustrate the efficiency and accuracy of this method.