A Track Initiation Method Based on Multiple Accumulation of Active Sonar Images
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摘要: 为满足强混响背景下水下运动目标自主检测要求, 针对主动声呐回波信号空时处理后数据量庞大的问题, 提出了一种基于主动声呐图像多重累积的航迹起始算法。首先, 构建主动声呐强混响背景下水下多目标航迹起始模型。通过声呐图像的择大累计, 将距离-方位-帧时间三维声呐图像压缩成距离-方位二维声呐图像, 并保留了累积帧信息。通过质心聚类点迹提取的方法, 获取目标量测信息和能量信息, 完成数据预处理。其次, 对Hough变换的参数空间进行能量累积, 并通过局部峰值检测的方法得到多目标初始航迹。最后, 为提高航迹准确率, 利用速度约束和航迹合并方法, 剔除了混响及合并重复航迹。仿真结果表明, 与常规的目标跟踪方法相比, 该算法有效降低了航迹起始过程中声呐图像的数据量, 在强混响背景下仍能以高检测概率实现水下多目标自主检测。Abstract: To meet the requirements of autonomous detection of underwater moving targets in a strong reverberation background, a track initiation algorithm based on multiple accumulations of active sonar images was proposed to solve the problem of large amounts of data after space-time processing of active sonar echo signals. Firstly, the underwater multi-target track initiation model in the strong reverberation background of the active sonar was constructed. The range-azimuth-frame time three-dimensional sonar image was condensed into the range-azimuth two-dimensional sonar image by selecting the largest data of sonar images, and the accumulated frame information was retained. The measurement information and energy information of the target were obtained through the centroid clustering point extraction method, and the data preprocessing was completed. Secondly, the energy was accumulated in the parameter space of the Hough transform, and the initial track of multiple targets was obtained by the method of local peak detection. Finally, in order to improve the accuracy of the track, the reverberation and duplicate tracks were eliminated by using the velocity constraint and track merging method. The simulation results show that compared with conventional target tracking methods, this algorithm can effectively reduce the amount of sonar image data in the course of track initiation and can still achieve autonomous detection of underwater multiple targets with high detection probability in a strong reverberation background.
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Key words:
- underwater multi-targets /
- active sonar /
- track before detection /
- Hough transform /
- track initiation
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图 3 具有噪声分布的声呐图像参数空间累积图(局部)
Figure 3. Spatial accumulation map of sonar image parameters with noise distribution(local)
图 4 10次择大累积后声呐序列图像
Figure 4. Sonar sequence image after maximum accumulation of 10 times
图 5 10次择大累积后量测数据点分布
Figure 5. Distribution of measurement data points after maximum accumulation of 10 times
图 6 质心聚类后量测数据点分布
Figure 6. Distribution of measurement data points after centroid clustering
表 1 目标运动参数
Table 1. Motion parameters of targets
编号 起始位置/km 航向(与x轴夹角)/(°) 信噪比
/dB目标1 (4, 9) 210 −15 ~ −13 目标2 (3.5, 7.8) 120 −13 ~ −15 目标3 (−1, 5) −30 −10 ~ −8 
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