Beamforming Methods of Nonlinear Filtering for Interference Signal Cancellation

The beamforming technology can be used to cancel interference signals coming from different incident angles for a uniform linear antenna array. Some beamforming techniques have been well developed, in which the generalized sidelobe canceller (GSC) can adaptively adjust the beamforming pattern for the desired signal to obtain maximum signal-to-interference-plus-noise ratio (SINR) and actually, it converts a constrained optimization beamforming problem into an un-constrainted one. Nevertheless, the GSC technique is very sensitive to the direction-of-arrival (DOA) mismatch of the desired signal. In this proposal, we model the DOA mismatch or moreover, the DOA change due to a moving source, into the GSC structure. Using the state-space formulation, three nonlinear filtering algorithms, i.e., the extended Kalman filter, the unscented Kalman filter, and the particle filter, will be developed and compared to solve the DOA mismatch problem in a decision feedback (DF) GSC beamforming structure. The actual DOA information is estimated by proposed algorithms and is provided to the GSC for improving SINR. System SINR and transmission performance will be explored in this project to study the proposed method.