基于矢量阵的鲁棒自适应舰船噪声检测算法研究

Robust adaptive ship noise detection algorithm based on vector array

稳健Capon波束形成算法直接将自适应对角元加载因子的计算与导向矢量的误差联系起来,易于实际操作,避免了其他算法计算加载量时的随意性。文章针对长线阵声纳检测近距离快速移动目标时观测数据不充分的问题,提出了一种基于矢量阵的改进稳健Capon波束形成算法。算法对数据矩阵进行奇异值分解,避免了求取不满秩的协方差矩阵,且减少了运算量及存储量。该算法对导向向量失配不敏感,且能有效地对快速移动的目标进行方位估计。最后通过仿真结果和海试试验数据处理验证了算法的有效性。

The Robust Capon Beamforming algorithm directly connects the calculation of the loading factor of the adaptive diagonal element with the error of the steering vector, which is easy to operate, and avoids the randomness of other algorithms when calculating the loading amount. In this paper, an improved Robust Capon Beamforming algorithm based on vector array is proposed to solve the problem of insufficient observation data when long linear array sonar detects close distance fast moving targets. The algorithm performs the singular value decomposition of the data matrix, avoids the covariance matrix of the incomplete rank, and reduces the amount of computation and storage. With the algorithm is insensitive to steering vector mismatch, and can effectively estimate the azimuth of fast moving targets. Finally, the simulation results and sea trial data processing verify the effectiveness of the algorithm.