小快拍数的线阵空时自适应处理方法

给出了一种用来进行抗混响的降雏空时自适应处理方法,尤其适合于在样本数据不足的情况下使用.该方法把待检测的空时数据划分为子组进行空时自适应处理,采用空时前后向平滑的方法来增加有效的样本数据数量,提高协方差矩阵的估计精度.对所有子组的输出进行相干叠加,不仅进一步提高了输出信混比,还减小了因子组处理而带来的空间和时间孔径的损失.利用实测运动声纳混响加仿真目标的方式对给出的方法性能进行了检验,表明该方法能够有效消除强混响,而且具有较高的稳健性.

Space-time adaptive processing for line array with a small number of snapshots

A reduced-rank space time adaptive processing(STAP) method for reverberation suppression is given,which is suitable for the case of lack of samples especially.The method carries out STAP after dividing the data to be detected into subgroups,and the number of valid samples increases greatly by using the techniques of spatial smoothing and temporal smoothing in forward /backward directions which will improve the estimating precision of the covariance matrix.The output signal to reverberation ratio can be improved by summing the outputs of all the subgroups coherently,and the loss in space-time aperture due to the processing of subgroup can be decreased.The performance of the given method is tested by using the trail reverberation data from a moving sonar in which a simulated target signal is added.It is shown that the method can eliminate the strong reverberation efficiently and has a higher robustness.