%0 Journal Article
%T A 2-D GLR Target Detection Approach of UWB SAR Based on Multi-resolution Feature<br>基于多分辨率特征的UWB SAR二维广义似然比目标检测方法
%A YANG Zhi-guo
%A HUANG Xiao-tao
%A ZHOU Zhi-min
%A <br>杨志国
%A 黄晓涛
%A 周智敏
%J 遥感学报
%D 2008
%I 
%X There are many features used to distinguish target from clutter in Synthetic Aperture Radar (SAR) target detection, such as amplitude feature, polarmi etric feature, azmi uthal feature, multi-resolution feature. There are many reports about the first three features, but there are very few reports about the developmentofmulti-resolution feature. The approaches proposed in concerned references are effective to mi prove the performance ofSAR targetdetection. Butmostof them discuss themulti-resolution feature for targetdetection ofhigh-frequency SAR, so the proposed approaches are com- monly suitable for the targetdetection ofhigh-frequency SAR. Ultra-W ide Band SyntheticAperture Radar (UWB SAR) can be used to detect the concealed targetsbecause itworks at low-frequency, and the corresponding detection background is the strong clutterproduced by trunks. The application ofmultiresolution feature inUWB SAR targetdetection are ana- lyzed, and the approaches suitable forUWB SAR targetdetection are proposed. In thispaper, we establish the equivalent models of target and trunk clutter inUWB SAR mi ages according to electromagnetic scattering theorybased on the particu- larity ofUWB SAR operation system. The differences between target and trunk clutter under differentmultiresolution are analyzed from UWB SAR mi age. The analysis supplies a key basis for the extraction ofmultiresolution feature in UWB SAR mi ages. Two formsof first-orderAuto-Regression (AR) modelare used to dealwith themultiresolution sequences. In the firstAR mode,l we discuss its statistic distribution of residual to represent the differences between target and trunk clutter. In the secondARmode,l we discuss its statistic distribution ofcoefficient to represent the differencesbetween tar- get and trunk clutter. In two forms of first-orderARmode,l the corresponding definitions ofGeneralized LikelihoodRatios (GLR) are given. The definition of2-D GLR is proposed based on two forms ofAR mode.l The performance of the 2-D GLR ismore robust in themultiresolution feature extraction because it integrates two forms of first-orderAR mode.l The three steps of2-D GLR calculation based onUWB SAR mi age are given: 1) generatingmultiresolution mi age sequences, 2) training statisticmode,l 3) calculating2-D GLR. Themultiresolution feature extraction expermi ent is accomplished in an actualUWB SAR mi age for the two 1-D GLRs and the 2-D GLR proposed in this paper. The results of the expermi ent show that themultiresolution features corresponding to the proposed threeGLRs can allbe used to mi prove the signal-clut- ter ratio (SCR) of the original mi age effectively, and the performance of the 2-D GLR is better than the two 1-D GLRs.
%K UWB
%K SAR
%K 目标检测
%K 多分辨率
%K AR模型
%K 广义似然比
%K 多分辨率
%K 特征提取
%K 广义似然比
%K 目标
%K 检测方法
%K Feature
%K Based
%K UWB
%K SAR
%K Approach
%K 检测效果
%K 信杂比
%K 增强图像
%K 利用
%K 结果
%K 试验
%K 稳定性
%K 计算方法
%K 建模
%K 序列
%K 模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=213CF71207DB87D444272B65DF1FFC86&yid=67289AFF6305E306&vid=59906B3B2830C2C5&iid=0B39A22176CE99FB&sid=1DF3F9D75A12D97B&eid=E2E0FBFE4D7EFB94&journal_id=1007-4619&journal_name=遥感学报&referenced_num=0&reference_num=15