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| 小孔径多波束声呐测深算法改进 |
| Improvement of small aperture multi-beam sonar bathymetry algorithm |
| 投稿时间：2023-04-06 修订日期：2023-09-28 |
| 中文摘要: |
| 多波束测深声呐采用多重信号分类算法能够在较小阵列尺寸的情况下保证较高的角度分辨率。然而，由于水底回波的边缘波束信噪比较低，多重信号分类算法伪谱中较强的伪峰干扰会导致后续测深算法的深度估计结果出现错误。针对该问题，提出一种基于最大信噪比的修正峰值搜索算法。该算法假定相邻波束的水底地形具有缓变性，选取回波信噪比最大的时刻，利用多重信号分类算法进行波达方向估计以获取信号角度、时间参考值。然后，分别向左右两侧利用时间期望值对回波信号进行加权与峰值搜索，实现更精确的测深。最后，通过实测数据验证了该文提出算法的有效性，该算法在特定条件下能够将边缘波束的最大测深误差减小25.85%，平均测深误差减小8.02%。 |
| 英文摘要: |
| The use of multiple signal classification (MUSIC) algorithm in multi-beam bathymetry sonar can ensure high angular resolution in small array sizes. However, due to low signal-to-noise ratios of edge beams of underwater echoes, strong pseudo peak interference in MUSIC pseudo spectrum will lead to errors in depth estimation results of subsequent bathymetry algorithms. To solve this problem, this paper proposes a modified peak search algorithm (MPSA) based on maximum signal-to-noise ratio. This algorithm assumes that the underwater terrain of adjacent beams has slow variability, selects the moment with the highest echo signal-to-noise ratio, and uses the MUSIC algorithm to estimate the direction of arrival to obtain the signal angle and time reference value. Then, the time expected value is used to weight and peak search the echo signal to the left and right sides respectively, achieving more accurate bathymetry. Finally, the effectiveness of the algorithm proposed in this paper was verified through actual measurements. Under specific conditions, the algorithm can reduce the maximum bathymetry error of the edge beam by 25.85% and the average bathymetry error by 8.02%. |
| DOI： |
| 中文关键词: 多波束测深声呐 小孔径阵列 多重信号分类算法 修正峰值搜索 |
| 英文关键词: Multi-beam bathymetry sonar Small aperture array Multiple signal classification algorithm Modified peak search |
| 基金项目: |
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