基于稀疏约束和SRV约束的宽带自适应波束形成

针对传统的宽带MVDR自适应波束形成中,抑制干扰的同时会抬高旁瓣电平,且过多的线性约束会导致波束输出的SINR性能下降的问题,提出了一种基于SRV约束和稀疏约束的低旁瓣、高增益宽带自适应波束形成方法.该方法在窄带MVDR自适应波束形成基础上,通过增加波束图稀疏约束来降低波束的旁瓣电平,同时利用空间响应偏差(SRV)约束将窄带算法推广到宽带MVDR 自适应波束形成中,极大地降低了算法的复杂度,改善了波束输出的SINR 性能.与传统方法相比,该方法在降低宽带波束的旁瓣电平的同时,还具有良好的干扰抑制效果.数值仿真实验验证了该方法的有效性.

Broadband Adaptive Beamforming Base on the Sparse Constraint and Spatial Response Variation Constraint

Regarding the problem of the high sidelobe level and output SINR performance degradation of conventional broadband adaptive beamformer due to interference suppression and over-constraints with a less number of degrees of freedom(DOF) for interference suppression,a novel broadband beamformer with low sidelobe level and high array gain is proposed by employing sparse constraint and the spatial response variation constraint(SRV).To suppress the sidelobe level of adaptive beamforming,sparse constraint on the beam pattern is added to the narrowband minimum variance distortionless response(MVDR) beamformer.Then the algorithm is extended to broadband adaptive beamforming by the spatial response variation constraint with low computational complexity and high output signal to interference noise ratio(SINR).Moreover,lower Peak sidelobe lever(PSL) and well effect of interference suppression can be achieved in comparison with traditional methods.The effectiveness of this new method is illustrated by a few numerical examples.