Sparse linear arrays for estimating and tracking DOAs of signals with known waveforms

There are two main ways by which antenna arrays can significantly improve the performance of the direction-of-arrival (DOA) estimation. In the first method, one can extend the array aperture by designing a sparse antennas array. The second method makes use of the temporal information of the received signals, such as the signal waveform. A few articles have dealt with DOA estimation by combining the above two approaches. In this paper, we present a DOA estimation and tracking method by employing the known waveform of the signal and the parallel recursive least square (RLS) technique. When the waveform of the signal is known, the output of each sensor in the array can be considered as a linear regression model of which the coefficients contain the whole information for estimating the DOA. Therefore, the RLS filter is used to estimate and track these coefficients and then the relationship among the coefficients of all the sensors is exploited to obtain the final DOA value without ambiguity. Finally, computer simulation of the proposed method with comparison to the previous methods is conducted.