Spatial averaging of time-frequency distributions for signal recovery in uniform linear arrays

This paper presents a new approach based on spatial time–frequency averaging for separating signals received by a uniform linear antenna array. In this approach, spatial averaging of the time–frequency distributions (TFDs) of the sensor data is performed at multiple time–frequency points. This averaging restores the diagonal structure of the source TFD matrix necessary for source separation. With spatial averaging, crossterms move from their off-diagonal positions in the source TFD matrix to become part of the matrix diagonal entries. It is shown that the proposed approach yields improved performance over the case when no spatial averaging is performed. Further, we demonstrate that in the context of source separation, the spatially averaged Wigner–Ville distribution outperforms the combined spatial–time–frequency averaged distributions, such as the one obtained by using the Choi–Williams distribution. Simulation examples involving the separation of two sources with close AM and FM modulations are presented.