Research On Methods And Applications Of Robust Beamforming With Little Dependency On Priori Information

The main fields of array signal processing include object detection and parameter estimation.Adaptive beamforming has been the indispensable method of choice to tackle these problems.The detection and parameter estimation performance of the array system degrade sharply in the presences of model mismatches and strong interferences.To improve the robustness of acoustic equipment in practical situation,theoretical and experimental studies on robust adaptive beamforming and array calibration technologies are carried out in this paper.The detailed research contents are as follows:1.The performance of the standard Capon beamformer becomes worse whenever there is a mismatch between the presumed signal vector and the actual one,a robust adaptive beamforming method based on least-square estimation is proposed.Also,considering the high computational-complexity of the second-order core program(SOCP),a solving method based on one-dimensional searching is presented.The standard Capon beamformer(SCB)is converted to robust least-square problem based on the principle of generalized sidelobe canceller,and then converted to second-order program problem.A one-dimensional search method is deduced using the relationship between the primal and dual problem of second-order program,Newton iteration method is adopted to obtain the optimal solution.Numerical simulation and experiential results show effectiveness of the proposed approach and its low sensibility against the parameter.The proposed algorithm is also extended to the acoustic vector array,Simulation results demonstrate that,compared with the common algorithm,the proposed algorithm can offers better performance in the presences of model mismatches and attitude error in particular.2.The performance of common robust adaptive beamforming degraded with the increasing degree of the signal steering vector error.To solve this problem,a robust adaptive beamforming based on searching optimal signal steering vector is proposed.The proposed algorithm could estimate the optimal steering vector automatically from the given data.The only prior information used in the proposed algorithm is the angular sector in which the interesting signal lies,which could be obtained easily in practical application.Numerical simulation and experiment results demonstrate the availability of the proposed algorithm in the case of steering vector mismatch and snapshot deficiency.Compared with common methods,the proposed method provides more sufficient robustness against large look direction error.3.In practical application,the position errors and attitude errors may exist simultaneously in the acoustic vector array.To alleviate this problem,a far-field self-calibration method based differential evolution(DE)is carried out.DE algorithms,inspired by Darwinian theory of evolution,are good at dealing with non-linear and complex optimization problems.The weighted subspace fitting estimator is employed to estimate the errors,and DE algorithm is applied to obtain the optimal solution.The only prior information used is the bound of the error.Numerical simulation results demonstrate its validity.4.Coherent methods for broadband adaptive beamforming which incorporate the focusing procedure plays a important role in parameter estimation of the broadband array signal processing.The main benefits of the coherent methods are low computation complexity and the ability to deal with coherent signal scenarios.However,for the inevitable focusing errors and look direction bias,focusing for the purpose of adaptive beamforming is a difficult task.To solve this problem,a robust coherent broadband beamforming of acoustic vector array is proposed.Firstly,we extend wavefield interpolated narrowband generated subspace(WINGS)focusing transformation to acoustic vector array.Then,robust strategy is used for the further process.Numerical simulation results show that the proposed algorithm could achieve low computational complexity,constant beam-width,and robustness against look direction errors.