Research On Robust Adaptive Beamforming Technology

Adaptive beamforming technology is one of branchs in space array signal processing,which is enhancing the desired signal without distortion,while suppressing the interference effectively.It has been widely used in radar,acoustics,medicine,wireless communications,and other fields.After decades of development,adaptive beamforming technology becomes more and more mature in theories,but in the practical engineering application,adaptive beamforming performance degradation or even the signal cancellation will occur due to the presence of various errors.Therefore,the robust adaptive beamforming technology becomes one of research hotspots.Research results related to the robust adaptive beamforming technology in this paper are as follows.Firstly a mathematical model of the received array signal is established,optimization criterion of the statistically optimal beamforming is gived,under the influence of errors,the reasons of adaptive beamforming technology appearing signal cancellation are discussed,which provide a theoretical basis for avoiding signal cancellation and improving the robustness.Secondly the classical robust technique of adaptive beamforming is analysed,and the robustness mechanism is studyed,then the advantages,disadvantages and applicable environmental of the robust algorithm are compared.Finally the simulation results show that the algorithms are robust against the desired signal steering vector mismatch.In the practical engineering applications,the training data often contains the desired signal,and from the perspective of signal cancellation,the interference noise covariance matrix estimation is an effective way to avoid signal cancellation.This paper presents a new method of the interference noise covariance matrix estimation,the method is suitable for the noise as the gaussian white noise,using the mean of smaller eignvalues from the received signal covariance matrix eigendecomposition as the noise power,the interference signal power spectrum getted from the steering vector,we can obtain the estimated interference noise covariance matrix.According to the subspace theory,this paper presents a robust adaptive beamforming algorithm,by making the projection of signal steering vector onto noise subspace optimized,a more accurate steering vector is obtained.Combining with the two algorithms,a robust beamforming method based on the interference noise covariance matrix estimation is proposed,the simulation results show that the algorithm can point to the correct direction of the desired signal,and has a higher output signal to interference plus noise power ratio.In the coherent interference environment,the rank loss of received signal covariance matrix will occur,which will seriously decrease the conventional algorithm's performance.To restore the rank of the covariance matrix,the classic spatial smoothing technique is described,the mechanism of decorrelation is analysed,then the study of both the theory and simulation validates its part decoherence capacity.Aiming at the shortcomings of the part decoherent,a new hybrid robust algorithm against the coherent interference environment is proposed.The algorithm adopt an iterative toeplitz method which has the fully decoherent.Without changing the characteristics structure of the received signal covariance matrix,the matrix toeplitz properties is restored,which achieves the effect of complete decoherence.Due to the limited snapshot data and the completely decoherent covariance matrix have the errors,therefore,the robust technology is applied by the errors and the desired signal steering vector errors are constrained to a constant,then calculate the weight vector which makes the smallest array output power under the constraints.the simulation results show that the algorithm can effectively suppress the coherent interference,have the robustness when the steering vector is mismatch,and have a higer output SINR than the spatial smoothing method.