High accuracy and low complexity adaptive Generalized Sidelobe Cancelers for colored noise scenarios

The Generalized Sidelobe Canceler (GSC) is a beamforming scheme which is applied in many fields such as audio, RADAR, SONAR and telecommunications. Recently, the adaptive Reduced Rank GSC (RR-GSC) has been proposed for applications with a large number of sensors. Due to its dimensionality reduction step, the adaptive RR-GSC achieves an enhanced performance in comparison with the standard GSC. However, both standard GSC and RR-GSC have their performance drastically degraded in the presence of colored noise. In this paper, we propose to extend further the GSC and the RR-GSC for colored noise scenarios. As shown in this paper, such improvement in colored noise scenarios can be obtained by incorporating a stochastic or a deterministic prewhitening step in the GSC and RR-GSC algorithms. Since the prewhitening increases the computational complexity, a block-wise reduced rank stochastic gradient GSC beamformer is also proposed. The block-wise step allows only one prewhitening step per block while in the previous schemes one per sample was needed. Another proposed advance in colored noise scenarios is the incorporation of the Vandermonde Invariance Transform (VIT). The VIT works as a pre-beamformer which reduces the interferent power of the undesired sources and the colored noise effect. We show by means of simulations the improved results even for highly correlated scenarios