基于压缩感知的单通道鲁棒自适应波束形成算法

针对在低快拍以及导向矢量存在误差等情况下自适应波束形成鲁棒性下降的问题，该文提出一种基于压缩感知(CS)的单通道鲁棒波束形成算法。首先提出一种新的单通道阵列体制，建立阵列信号压缩感知模型，并验证其感知矩阵满足约束等容(RIP)条件，在此基础上，采用快速的鲁棒平滑L0(RSL0)算法重构信号干扰矩阵，最后以表征阵列鲁棒性的阵列灵敏度作为目标函数，以干扰矩阵作为约束条件，形成有效波束。计算机仿真表明算法只需一个射频通道，即可在低快拍下有效抑制相干、非相干干扰信号，并可避免因通道间不一致造成的鲁棒性问题，验证了算法的有效性和优越性。

Compressive Sensing Based Single-channel Robust Adaptive Beamforming Algorithm

To solve the degradation of robustness against array steering vector error with finite snapshot in the adaptive beamformer, a novel single-channel robust adaptive beamforming algorithm based on Compressive Sensing (CS) is derived. A single-channel array system is first presented, and then the array signal module based on CS is build, in which the sensing matrix satisfies the Restricted Isometry Property (RIP). The signal and interference matrix can be recovered by fast Robust Smoothed L0 (RSL0) norm algorithm. Finally, the effective beam can be formed with the objective function and constraint setting to be array sensitivity function and interference matrix respectively.Computer simulation shows that the presented algorithm can suppress interferences with any coherence in case of one single-channel of radio frequency and finite snapshots, confirming the validity and superiority of the proposed algorithm.