一种适用于多输入多输出声呐的稳健空时自适应检测方法

针对多输入多输出声呐在水下探测场景中获得的空时快拍数量不足导致空时自适应检测性能下降的问题, 提出一种适用于小空时快拍数情况下的稳健空时自适应检测(STAD)方法。首先将斜对称特性推广到多输入多输出(MIMO)声呐空时自适应检测中, 并利用该特性将空时快拍数量扩展至原来的两倍; 然后利用迭代自适应方法实现对空时协方差矩阵的重构; 最后根据广义似然比检测(GLRT)准则推导出检验统计量。计算机仿真结果表明, 所提方法可以在小空时快拍数情况下准确估计空时协方差矩阵, 大幅减小空时自适应检测对空时快拍数量的需求, 提高多输入多输出声呐在小空时快拍数情况下的检测稳健性。 

A robust space-time adaptive detection method for multiple-input multiple-output sonar

The insufficient number of space-time snapshots collected by the Multiple-Input Multiple-Output (MIMO) sonar in the underwater target detection scene results in the performance degradation of Space-Time Adaptive Detection (STAD). To deal with this problem, a robust STAD method for the MIMO sonar is proposed. Firstly, the persymmetric structure is extended to the MIMO sonar and the number of space-time snapshots is expanded to twice the original through this structure; secondly, iterative adaptive approach is utilized to reconstruct the space-time covariance matrix; finally, the test statistic for the MIMO sonar is obtained based on the Generalized Likelihood Ratio Test (GLRT) criterion. Computer simulation results show that the proposed method can realize the accurate estimation of space-time covariance matrix, greatly reduce the demand of snapshots in STAD, and improve the robustness of target detection.