雷达科学与技术2025，Vol.23Issue(2)：167-175,9.DOI:10.3969/j.issn.1672-2337.2025.02.007
结合Fisher信息矩阵的方位角自适应SAR目标识别
Azimuth-Adaptive SAR Target Recognition Based on the Fisher Information Matrix
摘要
Abstract
Automatic target recognition(ATR),as an important means of synthetic aperture radar(SAR)image interpretation,has attracted much attention.Due to the large difference in the scattering characteristics distribution of SAR targets in different azimuth domains,the image characteristics of SAR targets are highly sensitive to the azimuth angle.Moreover,it is difficult for radar to capture all the azimuth domain data of the target in a single observation,and the recognition performance of the SAR-ATR model trained on past data is reduced on the newly observed azimuth do-main data.When the new observation data is arrived in the form of a stream,it is easy to cause the problem of"Cata-strophic Forgetting"if the existing model is retrained only by relying on the new observation data.Therefore,in this paper,the regularization term adjusted by Fisher information matrix is used to protect the model parameters that contrib-ute greatly to the recognition task,and the core set is used to reduce the inference error,so as to construct an azimuth adaptive continuous learning model for SAR target recognition.The experimental results show that the azimuth adaptive SAR-ATR model can learn the SAR target data under different azimuth angles online,continuously adapt to its feature changes,and effectively improve the generalization to the unobserved azimuth domain data.关键词
合成孔径雷达/自动目标识别/方位角域/连续学习/Fisher信息矩阵Key words
synthetic aperture radar/automatic target recognition/azimuth domain/continuous learning/Fisher information matrix分类
信息技术与安全科学引用本文复制引用
陈虹廷,武凡,杜川,龙伟军..结合Fisher信息矩阵的方位角自适应SAR目标识别[J].雷达科学与技术,2025,23(2):167-175,9.基金项目
国家自然科学基金(No.62071440) （No.62071440）
