子空间方法用于宽容的自适应波束形成

Subspace approach to robust adaptive beamforming

由于浅海波导和接收阵本身存在大量的不确实性,使得接收到的阵数据产生严重的失真,而常见的自适应波束形成方法如MVDR对失配很敏感。为此,本文提出了一种宽容性的自适应子空间波束形成方法。考虑一个具有空间特征的信号位于已知的子空间,但在子空间中的具体位置未知,并将干扰建模为子空间干扰。首先对未知参量进行最大似然估计,代入似然比检测中得到广义似然比检测(GLRT),从而得到子空间波束形成器。通过对不同失配情况下仿真以及实际海试数据处理验证了子空间波束形成器的性能,仿真和实验数据处理结果表明,子空间波束形成器比MVDR更宽容,比较明显提高检测和估计性能。

The data received by an array are severely distorted due to the uncertainty of the array itself and the nonstationary in the shallow water waveguide. The traditional adaptive beamformings such as the minimum-variance distortionless response （MVDR） are extremely sensitive to these mismatches. In this paper, a robust adaptive subspace beamforming is presented. It is assumed that the signal of interest belongs to a known linear subspace but that its coordinates within this subspace are otherwise unknown, and the interferences are also in some subspaces. First, the unknown parameters are estimated using maximum-likelihood estimator. Next, the maximum-likelihood estimates are used to derive a generalized likelihood ratio test （GLRT）. The GLRT detector is called subspace beaforming. The performance of the subspace beaforming is illustrated by means of simulations under the conditions of several kinds of mismatches and by the experimental in-sea data. The results of simulations and experimental data show that subspace offers an improved performance on estimation and detection and is more robust than MVDR.