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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。
In theory, the adaptive beamforming method has better target parameter estimation ability and interference suppression capability than the conventional beamforming method that does not depend on the input data. However, in actual underwater acoustic environment, the factors such as the acoustic propagation model, the receiving manifold array manifold and the signal statistical characteristics often have some differences with the actual situation, resulting in the performance degradation of the traditional adaptive beamforming method. Therefore, it is more and more important to improve the robustness of adaptive beamforming to these factors. Based on the idea of worst-case optimization and the improvement of MVDR constraints, this paper proposes a robust minimum-variance distortion-free adaptive beamforming algorithm (R-MVDR) The covariance matrix and the direction vector are analyzed. The performance of the beamforming weight vector and the spatial spectrum estimation is deduced. Finally, the experimental data are validated by the sea experiment. The results show that the proposed algorithm has better azimuth resolution and interference suppression in the real environment.