小样本SAR目标的双重一致性因果识别方法  

A Causal Interventional SAR ATR Method with Limited Data via Dual Consistency

作　　者：王陈炜 罗思懿 黄钰林 裴季方 张寅 杨建宇 WANG Chenwei;LUO Siyi;HUANG Yulin;PEI Jifang;ZHANG Yin;YANG Jianyu(School of Information and Communication Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China)

机构地区：[1]电子科技大学信息与通信工程学院,成都611731

出　　处：《电子与信息学报》2024年第10期3928-3935,共8页Journal of Electronics & Information Technology

基　　金：四川省自然科学基金(2023NSFSC1970)。

摘　　要：在小样本条件下提升方法的泛化性能,是合成孔径雷达自动目标识别(SAR ATR)的重要研究方向。针对该方向中的基础理论问题,该文建立了一个SAR ATR因果模型,证明了SAR图像中背景、相干斑等干扰在充足样本条件下可以被忽略;但在小样本条件下,这些因素将成为识别中的混杂因子,在提取的SAR图像特征中引入虚假相关性,影响SAR ATR性能。为了甄别和消除这些特征中的虚假效应,该文提出一个基于双重一致性的小样本SAR ATR方法,其中双重一致性包括类内一致性掩码和效应一致性损失。首先,基于鉴别特征应具有类内一致和类间差异的原则,利用类内一致性掩码,捕获目标的类内一致鉴别特征,甄别出目标特征中的混淆部分,准确估计出干扰引入的虚假效应。其次,基于不变风险最小化的思想,利用效应一致性损失,将经验风险最小化数据量需求转变为对效应相似度的度量需求,降低虚假效应消除对数据量的需求,消除特征中的虚假效应。因而,所提基于双重一致性的小样本SAR ATR方法可实现特征提取中的真实因果,实现准确的识别性能。两个基准数据集上的识别实验,验证了该方法的合理性和有效性,可提升小样本条件下SAR目标识别的性能。Improving the generalization performance of methods under limited sample conditions is an important research direction in Synthetic Aperture Radar Automatic Target Recognition(SAR ATR).Addressing the fundamental problem in this field,a causal model is established in this paper for SAR ATR,demonstrating that interferences in SAR images,such as background and speckle,can be neglected under sufficient sample conditions.However,under limited sample conditions,these factors become confounding variables,introducing spurious correlations into the extracted SAR image features and affecting the generalization of SAR ATR.To accurately identify and eliminate these spurious effects in the features,this paper proposes a limited-sample SAR ATR method via dual consistency,which includes an intra-class feature consistency mask and effect-consistency loss.Firstly,based on the principle that discriminative features should have intra-class consistency and inter-class differences,the intra-class feature consistency mask is used to capture the consistent discriminative features of the target,subtracting the confounded part in the target features,and identifying the spurious effects introduced by interferences.Secondly,based on the idea of invariant risk minimization,the effect-consistency loss transforms the data requirement of empirical risk minimization into a need for labeling the similarity among effects of different samples,reducing the data demand for eliminating spurious effects and removing the spurious effects in the features.Thus,the limited-sample SAR ATR method proposed in this paper achieves true causal feature extraction and accurate recognition performance.Experiments on two benchmark datasets validate the effectiveness of this method which can achieve superior performance of SAR target recognition with limited sample.

关 键 词：合成孔径雷达 自动目标识别 小样本 因果推断 

分 类 号：TN958[电子电信—信号与信息处理]