Adaptive Beamforming Based On Optimal Sparse Array Design

Adaptive beamforming is a core technique in array signal processing field.In order to suppress interferences and noise,and receive signal of interest correctly,Adaptive beamformer changes the weight vector of the antenna sensor adaptively by analyzing the received signal.The beamforming performance is not only dependent on the array weights but also on the array configuration,Therefore,beamforming should use both the array structure and array weights to achieve optimal output performance.Optimal sparse array design is a method that optimizes the sensor position to meet certain performance indicators,while reducing hardware development costs.At present,the research based on the optimal sparse array design mainly considers the performance of the beampattern.The research using the maximum output signal-to-interference-noise ratio or the maximum output signal-to-noise ratio as the design criterion is insufficient,and there are deficiencies in which the signal models are mostly point source models.In order to solve the above problems,this thesis focuses on designing the optimal sparse array based on the maximum output signal-to-noise ratio and the maximum output signal-to-noise ratio criteria.The main work and contributions of this thesis can be summarized as follows:First,This paper presents an optimal sparse array design algorithm considering the maximum SINR and beampattern performance.Our solution is based on finding the beamformer weight vector achieving maximum output signal-to-interference-plus-noise ratio.To control the sidelobes of the beampattern,quadratic fractional constraints are introduced to optimize the beamformer weights We formulate the array design problem as a reweighted ?₁-norm squared real-valued QCQP program,which is solved iteratively by using semidefinite relaxation?SDR?and linear fractional SDR together.The resulting array yields excellent beamforming performance and a beampattern with low sidelobes.Next,This paper proposes an optimal sparse array design algorithm based on distributed source signals,which is different from the existing sparse array design mainly aimed at point source signals.Our proposed method is aimed at adaptive beamforming of spatial CD sources in the active environment,and establishes a sparse array design problem based on the maximum output signal-to-interference and noise ratio?SINR?.Also use sequential convex optimization methods to solve non-convex optimization problems,and analyzes the influence of angle distribution on array structure.At last,An optimal sparse array design algorithm based on wideband beamforming is proposed.From the perspective of maximizing SNR,the optimization problem is constructed by maximizing the ?₂-norm of signal covariance matrix,and two convex relaxation methods are introduced,namely,affine approximation method and iterative linear fractional programming method.The output SNR performance of the sparse array designed by two convex relaxation algorithms is analyzed,and the influence of different incident angles on the algorithm is studied influence.