一种基于Bayesian方法的鲁棒自适应波束形成算法

由于在实际环境中,期望信号的阵列响应与实际阵列响应之间存在偏差,使得现存的一些自适应波束形成算法的性能下降.针对上述问题,基于Bayesian方法提出了鲁棒自适应波束形成算法,并且给出其递推形式.该算法利用接收到的采样信号对实际信号方向向量进行估计,降低了信号到来方向的不确定性,对信号方向向量的偏差具有较强的鲁棒性,从而可以保证输出阵列的信干噪比接近最优值.采用递推方法来计算逆矩阵,大大地降低了计算的复杂度,能够满足实时处理的要求.仿真实验表明,与传统自适应波束形成算法相比,所提鲁棒自适应波束形成算法具有更好的性能.

Robust Adaptive Beamforming Algorithm Based on a Bayesian Approach

When applying adaptive arrays to actualities,the performance of existing adaptive array algorithms degenerates substantially because of the slight mismatch between actual and presumed array responses to expected signal.With the recursive process given,a novel robust adaptive beamforming algorithm is therefore proposed using Bayesian approach to respond to the current environment by learning or estimating the direction of arrival(DOA) of the actual signal from observations.The computational complexity of the proposed algorithm can thus be efficiently reduced in comparison with other algorithms since the recursive method is used to obtain inverse matrix,and it can provide excellent robustness for the uncertainty of DOA of actual signal and make the mean output array SINR consistently close to the optimal one.Simulation results reveal that the algorithm proposed is superior in performance to conventional ones.