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阵元位置误差的存在会严重影响水听器阵列的测向性能,为此在使用阵列之前需对该误差进行校正。针对这一需求,提出了一种对任意阵型适用的高精度阵元位置有源校正方法。结合远场阵列模型以及位置误差“有界”的特点,基于压缩感知理论,将阵元位置估计转化为对稀疏信号的重构过程,建立了阵元位置误差模型,构造了该模型下凸优化函数,并采用l_1-SVD(Singular Value Decomposition,SVD)方法进行求解,同时给出了物理解释和算法实施步骤。计算机仿真表明基于稀疏信号重构的校正方法性能明显高于子空间拟合算法,且性能接近相应克拉美罗下界,对于校正源方位误差有较强的容错能力,不受制于微小误差的假设以及初值的选取。该方法是一种可对阵列中的部分或全部阵元进行校正的高精度、稳健的有源校正算法。
The existence of array element position error will seriously affect the hydrophone array’s DF performance. Therefore, this error needs to be corrected before using the array. In response to this demand, a method of active calibration of high-precision array elements is proposed. Combined with the characteristics of the far-field array model and the position error “bounded ”, based on the compressed sensing theory, the position estimation of the array element is transformed into the reconstruction of the sparse signal, and the position error model of the array element is established. Under the model Convex optimization function, and solved by the Singular Value Decomposition (SVD) method. At the same time, the physical interpretation and algorithm implementation steps are given. Computer simulations show that the performance of calibration method based on sparse signal reconstruction is significantly higher than that of subspace fitting algorithm, and its performance is close to the corresponding Keramide lower bound. It has strong fault tolerance for the correction of source azimuth error, not subject to the assumption of slight error and The initial value of the selection. This method is a highly accurate and robust active calibration algorithm that can correct some or all of the array elements in the array.