非理想条件下基于矢量水听器阵列的一种快速方位估计算法

为了实现少快拍、低信噪比(SNR)条件下的水下目标快速方位估计，该文建立矢量水听器阵列方位估计稀疏表示模型。利用实值转化技术将复数方向矩阵转化到实数域，以便利用平滑L0算法对稀疏信号矩阵进行重构从而得到方位估计结果。该文改进平滑L0算法，利用收敛性更好的复合反比例函数(CIPF)函数作为平滑函数以及提出促稀疏加权的方法，该方法通过加权的方式修正噪声条件下L2范数作为迭代初始值偏离稀疏解较远的问题来促进算法快速收敛于稀疏解。通过仿真验证了该文提出的基于实值转换的促稀疏加权平滑L0算法在少快拍、低信噪比的条件下可以实现优于传统子空间类算法的性能，并且在保证性能的同时，显著提高方位估计的速度。

A Fast Direction Estimation Algorithm Based on Vector Hydrophone Array under Non-ideal Conditions

In order to realize the fast direction estimation of underwater targets under the conditions of less snapshot and low SNR, a sparse decomposition model of vector hydrophone array direction estimation is established. The real value conversion technique is used to convert the complex direction matrix into the real number field, so as to reconstruct the sparse signal matrix using the SL0 algorithm to obtain the orientation estimation result. The SL0 algorithm is improved, the Compound Inverse Proportional Function (CIPF) with better convergence is used as a smoothing function, and a weighted method is proposed which can promote sparsity, the weighted method is used to correct the problem that the norm as the initial iteration value deviates far from the sparse solution to increase the speed of azimuth estimation. The simulation verifies that the proposed algorithm can achieve better performance than the traditional subspace algorithm under the conditions of low snapshot and low SNR, and improve the speed of bearing estimation while ensuring performance.