Robust Adaptive Beamforming Using Modified Generalized Sidelobe Canceller Under Non-ideal Environments
Date Issued
2015
Date
2015
Author(s)
Liao, Ching-Wei
Abstract
LCMV (Linearly Constrained Minimum Variance) beamformer is one of the important and basic techniques in the antenna array signal processing. It aims to find the optimal solution for the weight vector by maintaining the desired array response while minimizing the array output power. Thus, the beamformer has a great ability to suppress interference and noise. The GSC (Generalized Sidelobe Canceller) derived from LCMV beamformer provides a simple way for implementing and makes the implementation of the LCMV much more efficient. However, the performance of the aforementioned beamformers is known to be degraded dramatically in the presence of steering vector error because of the signal cancellation phenomenon which leads the desired signal to be suppressed as interference. To improve the robustness, we propose a method called MGSC (modified GSC) evolved from the GSC. The MGSC uses a novel block matrix which can not only avoids the signal cancellation phenomenon but also decreases the computational complexity by diminishing the size of the adaptive weight vector. We also give the MGSC an ability to estimate steering vector and it only needs few computations. Then, we propose a way to make the MGSC combined with the existing algorithms. It can also improve the performance and decrease the computational complexity at the same time. Finally, we combine spatial smoothing technique with the MGSC to against coherent interference and steering vector error simultaneously.
Subjects
robust adaptive beamforming
steering vector estimation
generalized sidelobe canceller
signal cancellation phenomenon
steering vector error
coherent environment
Type
thesis
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