智慧型天線波束形成技術利用廣義旁帶消除器(Generalized Sidelobe Canceller, GSC)將限制最佳化問題轉為等效的無限制問題，讓想要接收的訊號能獲得最大的增益並盡可能去壓抑干擾訊號。由於GSC 系統對於入射角度預測誤差造的相位誤差很敏感，本計畫利用狀態估測的方式，研究三種非線性可適性演算法: 延展型卡爾曼濾波器 (Extented Kalman Filter)、非察覺型卡爾曼濾波器 (Unscented Kalman Filter)、及粒子濾波器 (Particle Filter)，利用所設計的決策回授GSC 系統透過可適性的方法解決預測訊號入射角度誤差所造成的影響。另外，由於可對狀態預測訊號角度作追蹤，所以當訊號源是移動性的情況下，同樣能使系統因相位誤差的影響降低。為了驗證我們所提出新的方法，本計畫將會模擬分析系統的SINR 性能。 ;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.
