一种鲁棒性的最小方差无失真响应波束形成算法及其应用

A robust minimum variance distortionless response algorithm and its application

理论上,自适应波束形成方法要比不依赖于输入数据的常规波束形成方法有更好的目标参数估计能力和干扰抑制能力。但在实际水声环境中,声传播模型、接收阵阵列流形以及信号统计特征等因素往往与实际情况存在一定的差异,导致传统的自适应波束形成方法性能下降。因此,提高自适应波束形成方法对上述因素的鲁棒性变得越来越重要。本文基于最差条件最优化的思想,改进MVDR(最小方差无失真响应)方法的约束条件提出了一种鲁棒性最小方差无失真响应自适应波束形成算法(R-MVDR),并对输入数据协方差矩阵和方向向量存在不确定性的情况进行了性能分析,推导给出了波束形成的加权向量和空间谱估计表达式,最后通过海上实验数据进行了验证。结果证明本文提出的算法在实际环境中有更好的方位分辨能力和干扰抑制能力。

Generally, the adaptive beamformer has better spatial resolution and much better interference rejection capability than the conventional data-independent beamformer. But in practice, the performance of the traditional adaptive beamformer will degrade greatly if some assumptions or information on the propagation model, array parameters and signal model are imprecise. Therefore, it is very important to make the adaptive beamforming techniques less sensitive to the model mismatch and parameter uncertainties. In this paper, we propose a robust minimum variance distortionless response （R-MVDR） algorithm based on the worst-case performance optimization changing the constraint of MVDR. The analytic expression for the optimized weight vector is presented. The performance of R-MVDR is verified via the numerical and experimental results. It can be demonstrated that the arithmetic proposed has better spatial resolution and much better interference rejection capability with experimental data.