Research On Key Techniques Of Robust Adaptive Beamforming

The array signal processing as an important branch of the signal processing domain is applied for many areas such as rada, sonar, communication and biomedical testing. Robust adaptive beamforming of antenna array is a significant aspect of research on array signal processing whose aim is to maximum the signal-interference-noise ratio by retaining the desired signal while inhibitig the jamming signal effectively. The adaptive array signal processing can obtain good performance in the ideal case. But the errors such as array element positions mismatch, inconsistent channel gains, finite snapshots and array element mutual coupling in the system always severely affect the performance of the array signal processing. So many researchers are trying to research robust adaptive array signal processing algorithms. This paper introduced several algorithms to improve the robusness.The errors affecting the system include array element positions mismatch, inconsistent channel gains, finite snapshots, array element mutual coupling. The mismatched matrix of element positions mismatch and inconsistent channel gains is random, but the mismatched matrix of array element mutual coupling is determined by the structure of array, so the mismatched covariance matrix can be preprocessed before calculating the optimum weight vector.The former algorithms including orthogonal projection algorithm, bayesian algorithm, sample matrix inversion algorithm, recursive least squares estimation algorithm, least mean square algorithm are introduced before introducing the amended diagonal loading algorithm. Compared with the traditional beamformer, the new algorithm outperforms in two sides. One is that all kinds of errors are considered with the correct math models. These errors include array element positions mismatch, inconsistent channel gains, finite snapshots, array element mutual coupling. On the other hand, the covariance matrix is preprocessed before calculating the optimum diagonal loading factor, which could get rid of some errors and improve the performance of diagonal loading method. The error models, approaches of preprocessing and diagonal loading factor calculating are proposed. Furthermore, the simulations certify the virtue of the new algorithm.A powerful adaptive beamforming algorithm based on convex in the presence of the pointing error is proposed by probabilistic constraints, aiming at the shortcoming of the sensitivity to the pointing error. It is under the assumption that the random steering vector mismatch has Gaussian distribution, we guarantee that the pointing constraint is greater than unit response with some selected probability. Then by convex approximation, the original problem is converted to an iterative second-order cone programming problem, which can be solved efficiently via well-established interative solution is also provided. Compared to existing approaches, our proposed method take into account all exsited errors including array element positions mismatch, inconsistent channel gains, finite snapshots and array element mutual coupling and the mismatched covariance matrix can be preprocessed before calculating the optimum weight vector through iteration.