研究多视图相关性及数据融合表征方法在舰船航迹中的应用，获取较准确的舰船航迹。应用基于CPLD的数据采集卡精准、高效采集多传感器舰船航迹数据，经基于LMD的新阈值函数小波去噪方法去除舰船航迹数据噪声，降低噪声干扰后，采用多视图相关性分析方法有效关联多个传感器数据，度量舰船航迹数据关联度，并以所获舰船航迹数据关联度为可靠依据，使用自适应数字滤波算法完成舰船航迹数据融合表征。实验结果表明：该方法可有效采集、去噪处理舰船航迹数据，舰船航迹数据融合的准确性高，在编队间距较小、目标密集度较高状态下均可获取较高的关联度，并有效获取目标舰船航迹。
The application of multi view correlation and data fusion representation method in ship track is studied to obtain more accurate ship track. The data acquisition card based on CPLD is used to accurately and efficiently collect multi-sensor ship track data. After the noise of ship track data is removed and the noise interference is reduced by the new threshold function wavelet denoising method based on LMD, the multi view correlation analysis method is used to effectively correlate multiple sensor data, measure the correlation degree of ship track data, and take the correlation degree of ship track data as a reliable basis. The adaptive digital filtering algorithm is used to complete the data fusion characterization of ship track. The experimental results show that this method can effectively collect and denoise the ship track data, and the accuracy of ship track data fusion is high. When the formation spacing is small and the target density is high, it can obtain a high correlation degree, and effectively obtain the target ship track.
2022,44(12): 145-148 收稿日期：2022-01-07
DOI：10.3404/j.issn.1672-7649.2022.12.029
分类号：TP391
作者简介：郑婷一(1987-)，女，博士，讲师，研究方向为数据挖掘
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