方位历程图是声呐中阵列信号处理中的重要参考结果。从方位历程图中提取可能存在的轨迹，对于后续的识别及跟踪处理具有重要的价值。在此背景下，本文提出一种根据时间、角度、功率三维信息融合的目标轨迹提取算法。该算法具体包含峰值筛选、聚类中心提取、轨迹关联及筛选、插值补充、相似去除、卡尔曼平滑等一系列步骤。具有通过数据自适应调整门限，不需要人为设置以及通过三维信息自适应识别交叉轨迹等优点。并对方位历程图数据进行多目标轨迹提取验证。结果表明采用该算法可以对高于环境背景噪声级的可疑轨迹进行有效提取。
The bearing-time recording is an important reference result in array signal processing in sonar. Extracting possible trajectories from the bearing-time recording is of great value for identification and tracking processing. In this context, a target trajectory extraction algorithm based on the fusion of three-dimensional information of time, angle and power is proposed. The algorithm specifically includes a series of steps such as peak screening, cluster center extraction, trajectory association and screening, interpolation supplementation, similarity removal, and Kalman smoothing. It has the advantages of adaptively adjusting the threshold through data without manual setting; adaptively identifying cross trajectories through three-dimensional information. Multi-target trajectory extraction was verified on the data of bearing-time map. The results show that the algorithm can effectively extract suspicious trajectories that are higher than the environmental background noise level.
2026,48(1): 159-164 收稿日期：2025-4-16
DOI：10.3404/j.issn.1672-7649.2026.01.023
分类号：U666.7
基金项目：国家自然科学基金资助项目（12304501）
作者简介：孙向伯(1999-),男,硕士研究生,研究方向为水声信号处理
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