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为了实现矢量水听器垂直阵列对目标的高分辨方位估计,提出了基于MUSIC子频带最优加权数据融合方法。该方法采用MUSIC算法对划分的各窄带信号进行方位估计,并在各子频带对多基元方位估计结果进行最优加权最小二乘融合处理,最后通过加权直方图统计法得到最终方位估计结果。对算法进行的仿真及海上试验数据处理结果表明:本文算法在方位估计精度、方位估计正确概率、多目标分辨以及对噪声子频带的抑制能力方面都优于单个基元MUSIC以及多基元复声强器融合算法。
In order to achieve high resolution azimuth estimation of the target vector hydrophone vertical array, an optimal weighted data fusion method based on MUSIC sub-band is proposed. In this method, the MUSIC algorithm is used to estimate the azimuth of each narrowband signal and the optimal weighted least-squares fusion is used to estimate the multi-cell azimuths in each sub-band. Finally, the final azimuth estimation results are obtained by weighted histogram statistics. Simulation of the algorithm and experimental data processing at sea show that the proposed algorithm is superior to single-element MUSIC and multi-element polyphony in azimuth estimation accuracy, azimuth estimation of correct probability, multi-target resolution and noise sub-band rejection Strong fusion algorithm.