一种改进的非相干紧凑偏振分解算法

IF 8.6 1区 地球科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Geoscience and Remote Sensing Pub Date : 2025-02-24 DOI:10.1109/TGRS.2025.3545022
Wentao An;Yarong Zou;Qian Feng
{"title":"一种改进的非相干紧凑偏振分解算法","authors":"Wentao An;Yarong Zou;Qian Feng","doi":"10.1109/TGRS.2025.3545022","DOIUrl":null,"url":null,"abstract":"For circular polarization transmitting linear polarization receiving (CTLR) compact polarimetric (CP) synthetic aperture radar (SAR) data, the volume scattering power proportion derived through CP decomposition, such as the <inline-formula> <tex-math>$m\\text {-}\\alpha $ </tex-math></inline-formula> decomposition algorithm, is typically overestimated. To address this issue, this study initially presents a theoretical analysis of the reason behind the overestimation of the volume scattering power proportion. The theoretical analysis reveals that the assumption “the volume scattering power proportion is <inline-formula> <tex-math>$1\\text {-}m$ </tex-math></inline-formula>” employed by the <inline-formula> <tex-math>$m-\\alpha $ </tex-math></inline-formula> decomposition indeed leads to an overestimation, where m represents the degree of polarization. Subsequently, a novel and smaller form of the volume scattering power proportion has been discovered, namely (<inline-formula> <tex-math>$1\\text {-}m)^{2}$ </tex-math></inline-formula>. Based on this finding, a modified <inline-formula> <tex-math>$m\\text {-}\\alpha $ </tex-math></inline-formula> decomposition algorithm has been proposed. Experiments were conducted using two fully polarimetric SAR images and a CP SAR image acquired by E-SAR, GF-3, and RISAT. The experimental results demonstrate that: 1) (<inline-formula> <tex-math>$1\\text {-}m)^{2}$ </tex-math></inline-formula> is statistically closer to the actual volume scattering power proportion than <inline-formula> <tex-math>$1\\text {-}m$ </tex-math></inline-formula>; 2) the decomposition performance of the modified <inline-formula> <tex-math>$m\\text {-}\\alpha $ </tex-math></inline-formula> decomposition algorithm surpasses that of the other six compact decomposition algorithms; and 3) employing the new volume scattering power proportion (<inline-formula> <tex-math>$1\\text {-}m)^{2}$ </tex-math></inline-formula> effectively mitigates the issue of volume scattering power overestimation in CP decomposition.","PeriodicalId":13213,"journal":{"name":"IEEE Transactions on Geoscience and Remote Sensing","volume":"63 ","pages":"1-13"},"PeriodicalIF":8.6000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Modified Incoherent Compact Polarimetric Decomposition Algorithm\",\"authors\":\"Wentao An;Yarong Zou;Qian Feng\",\"doi\":\"10.1109/TGRS.2025.3545022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For circular polarization transmitting linear polarization receiving (CTLR) compact polarimetric (CP) synthetic aperture radar (SAR) data, the volume scattering power proportion derived through CP decomposition, such as the <inline-formula> <tex-math>$m\\\\text {-}\\\\alpha $ </tex-math></inline-formula> decomposition algorithm, is typically overestimated. To address this issue, this study initially presents a theoretical analysis of the reason behind the overestimation of the volume scattering power proportion. The theoretical analysis reveals that the assumption “the volume scattering power proportion is <inline-formula> <tex-math>$1\\\\text {-}m$ </tex-math></inline-formula>” employed by the <inline-formula> <tex-math>$m-\\\\alpha $ </tex-math></inline-formula> decomposition indeed leads to an overestimation, where m represents the degree of polarization. Subsequently, a novel and smaller form of the volume scattering power proportion has been discovered, namely (<inline-formula> <tex-math>$1\\\\text {-}m)^{2}$ </tex-math></inline-formula>. Based on this finding, a modified <inline-formula> <tex-math>$m\\\\text {-}\\\\alpha $ </tex-math></inline-formula> decomposition algorithm has been proposed. Experiments were conducted using two fully polarimetric SAR images and a CP SAR image acquired by E-SAR, GF-3, and RISAT. The experimental results demonstrate that: 1) (<inline-formula> <tex-math>$1\\\\text {-}m)^{2}$ </tex-math></inline-formula> is statistically closer to the actual volume scattering power proportion than <inline-formula> <tex-math>$1\\\\text {-}m$ </tex-math></inline-formula>; 2) the decomposition performance of the modified <inline-formula> <tex-math>$m\\\\text {-}\\\\alpha $ </tex-math></inline-formula> decomposition algorithm surpasses that of the other six compact decomposition algorithms; and 3) employing the new volume scattering power proportion (<inline-formula> <tex-math>$1\\\\text {-}m)^{2}$ </tex-math></inline-formula> effectively mitigates the issue of volume scattering power overestimation in CP decomposition.\",\"PeriodicalId\":13213,\"journal\":{\"name\":\"IEEE Transactions on Geoscience and Remote Sensing\",\"volume\":\"63 \",\"pages\":\"1-13\"},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2025-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Geoscience and Remote Sensing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10900557/\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Geoscience and Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10900557/","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

对于圆极化发射线极化接收(CTLR)紧凑极化(CP)合成孔径雷达(SAR)数据,采用$m\text {-}\alpha $分解算法进行CP分解得到的体积散射功率比通常会被高估。为了解决这一问题,本研究首先从理论上分析了体积散射功率比高估的原因。理论分析表明,$m-\alpha $分解所采用的“体积散射功率比为$1\text {-}m$”的假设确实会导致高估,其中m代表极化程度。随后,发现了体积散射功率比的一种新颖且更小的形式,即($1\text {-}m)^{2}$。在此基础上,提出了一种改进的$m\text {-}\alpha $分解算法。实验采用E-SAR、GF-3和RISAT采集的两幅全极化SAR图像和一幅CP SAR图像。实验结果表明:1)($1\text {-}m)^{2}$在统计上比$1\text {-}m$更接近实际体积散射功率比;2)改进的$m\text {-}\alpha $分解算法的分解性能优于其他6种紧凑分解算法;3)采用新的体积散射功率比($1\text {-}m)^{2}$,有效地缓解了CP分解中体积散射功率估计过高的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A Modified Incoherent Compact Polarimetric Decomposition Algorithm
For circular polarization transmitting linear polarization receiving (CTLR) compact polarimetric (CP) synthetic aperture radar (SAR) data, the volume scattering power proportion derived through CP decomposition, such as the $m\text {-}\alpha $ decomposition algorithm, is typically overestimated. To address this issue, this study initially presents a theoretical analysis of the reason behind the overestimation of the volume scattering power proportion. The theoretical analysis reveals that the assumption “the volume scattering power proportion is $1\text {-}m$ ” employed by the $m-\alpha $ decomposition indeed leads to an overestimation, where m represents the degree of polarization. Subsequently, a novel and smaller form of the volume scattering power proportion has been discovered, namely ( $1\text {-}m)^{2}$ . Based on this finding, a modified $m\text {-}\alpha $ decomposition algorithm has been proposed. Experiments were conducted using two fully polarimetric SAR images and a CP SAR image acquired by E-SAR, GF-3, and RISAT. The experimental results demonstrate that: 1) ( $1\text {-}m)^{2}$ is statistically closer to the actual volume scattering power proportion than $1\text {-}m$ ; 2) the decomposition performance of the modified $m\text {-}\alpha $ decomposition algorithm surpasses that of the other six compact decomposition algorithms; and 3) employing the new volume scattering power proportion ( $1\text {-}m)^{2}$ effectively mitigates the issue of volume scattering power overestimation in CP decomposition.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing 工程技术-地球化学与地球物理
CiteScore
11.50
自引率
28.00%
发文量
1912
审稿时长
4.0 months
期刊介绍: IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.
期刊最新文献
Fine-Scale Structure Reconstruction of Weather Radar Echoes via Blind Super-Resolution Generalized Iterative Sparse Maximum Likelihood Algorithm for the Detection of Buried Targets Unsupervised Snowy-Weather Point Cloud Denoising via Two-Stage Filter-Network Collaboration Noise2Map: End-to-End Diffusion Model for Semantic Segmentation and Change Detection OAADet: One-stage Anchor-free Arbitrary Oriented Object Detector via Center-ness Shift Correction
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1