Direction estimation using conjugate cyclic cross-correlation: more signals than sensors

We consider the problem of estimating the directions of arrival of multiple communication signals arriving at a uniform linear array. By considering the conjugate cyclic cross-correlations of the sensor outputs and using a Bayesian framework, we propose a direction finding algorithm that allows us to estimate the directions of arrival for a more signals than sensors scenario. The algorithm does not need any training sequence and only requires a priori knowledge of the cyclic frequencies and the number of sources. It is also possible to estimate the directions of arrival in a multipath fading environment under certain conditions