Adaptive cyclostationary array beamforming with robust capabilities

The existing techniques exploiting the signal cyclostationarity have been shown to be effective in performing antenna array beamforming without requiring the steering information. However, these techniques suffer from performance degradation due to both cycle frequency error (CFE) for the desired signal and finite data sample (FDS) effects. To deal with the CFE, we present an iterative averaging (IA) scheme to estimate the actual cyclic correlation matrix. With regard to the effect of cycle leakage due to finite data samples, we develop a novel fully data-dependent diagonal loading (NFD-DL) scheme to estimate the actual data correlation matrix. Then, a novel method is developed based on the IA scheme in conjunction with the NFD-DL scheme to possess the robust capabilities against the CFE and the FDS effects simultaneously. The simulation results show that the proposed method outperforms the existing methods in dealing with antenna array beamforming for cyclostationary signals in the presence of both CFE and FDS effects.