AIS和光学遥感图像引导的星载SAR舰船目标识别网络
收稿日期: 2023-03-09
修回日期: 2023-04-12
录用日期: 2023-05-30
网络出版日期: 2023-05-31
基金资助
青年科学基金(62001499);国家自然科学基金(61790554)
Spaceborne SAR ship target recognition network guided by AIS and optical remote sensing images
Received date: 2023-03-09
Revised date: 2023-04-12
Accepted date: 2023-05-30
Online published: 2023-05-31
Supported by
National Science Fund for Young Scholars(62001499);National Natural Science Foundation of China(61790554)
星载SAR作为全天时、全天候的感知手段广泛应用于海洋目标识别任务中，由于SAR图像分辨率低、难解译、样本不均衡导致现有单一模态目标识别算法识别精度低。提出了一种AIS和光学遥感图像引导的星载SAR舰船目标识别网络，针对不同模态数据特征维度不同导致难度量问题，利用特征迁移模块在保留各自模态独有特征属性前提下将异构特征映射到共同的空间中度量；针对不同模态不同类别数据存在样本不均衡问题，利用异构特征对齐模块充分挖掘不同模态的互补信息，以细粒度的方式进一步对齐不同模态的异构特征，同时将各个模态的判别性特征作为先验信息迁移至SAR图像模态中。实验部分利用AIS历史数据和光学遥感数据集作为辅助信息，在2个公开的SAR图像舰船目标数据集中进行测试，实验结果表明所提算法通过迁移不同模态信息，有效提升了SAR图像舰船目标的识别准确率。
王子玲 , 熊振宇 , 杨璐铖 , 杨蕊宁 , 黄林周 . AIS和光学遥感图像引导的星载SAR舰船目标识别网络[J]. 航空学报, 2024 , 45(2) : 328672 -328672 . DOI: 10.7527/S1000-6893.2023.28672
Spaceborne SAR is widely used in marine target recognition tasks as an all-season and all-weather sensing means. Due to the low resolution， difficult interpretation and uneven samples of SAR images， the existing single-mode target recognition algorithms have low recognition accuracy. In this paper， a spaceborne SAR ship target recognition network guided by AIS and optical remote sensing images is proposed. To overcome the difficulty caused by different feature dimensions of different modal data， the heterogeneous features are mapped into the common space measurement by using the feature migration module on the premise of preserving the unique feature attributes of each modal. For the problem of sample imbalance in different modes and different categories of data， the heterogeneous feature alignment module is used to fully mine the complementary information of different modes， further align the heterogeneous features of different modes in a fine-grained way， and migrate the discriminant features of each mode as a priori information to SAR image modes. In the experimental part， AIS historical data and optical remote sensing data set are used as auxiliary information on two public SAR image ship target data sets. The experimental results show that the network proposed can effectively improve the recognition accuracy of ship targets in SAR images by fusing different modal information.
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