基于PCA算法的星载GNSS-R海面目标反演  

Inversion of Sea Surface Target of Spaceborne GNSS-R Based on PCA Algorithm

作　　者：胡媛[1] 顾世森 刘卫[2] 江志豪 袁鑫泰 HU Yuan;GU Shisen;LIU Wei;JIANG Zhihao;YUAN Xintai(College of Engineering Science and Technology,Shanghai Ocean University,999 Huchenghuan Road,Shanghai 201306,China;Merchant Marine College,Shanghai Maritime University,1550 Haigang Road,Shanghai 201306,China)

机构地区：[1]上海海洋大学工程学院,上海市201306 [2]上海海事大学商船学院,上海市201306

出　　处：《大地测量与地球动力学》2022年第10期991-994,共4页Journal of Geodesy and Geodynamics

基　　金：国家自然科学基金(52071199);上海市自然科学基金(19ZR1422800);上海市智能信息处理重点实验室开放基金(IIPL201904)。

摘　　要：提出使用主成分分析(principal components analysis,PCA)抑制时延多普勒图(delay Doppler map,DDM)中的海杂波,提高海面目标反演精度。以挪威Sn hvit采气平台作为海面目标,采用2016-11-13的DDM数据进行目标反演。结果显示,未使用PCA抑制海杂波前,反演位置平均误差为17.65 km;抑制海杂波后,反演位置平均误差为11.42 km,位置精度提升35.30%。To suppress the sea clutter in delay Doppler map(DDM)and improve the accuracy of sea surface target inversion,we propose principal components analysis(PCA).In this paper,the Norwegian Sn hvit gas platform is used as the sea surface target,and the DDM data on November 13,2016,are used for target inversion.Before using PCA to suppress sea clutter,the average error of inversion position is 17.65 km,the average error of inversion position after suppressing sea clutter is 11.42 km,and the position accuracy is improved by 35.30%.

关 键 词：GNSS-R 时延多普勒图 PCA 雅可比矩阵 目标反演 

分 类 号：P228[天文地球—大地测量学与测量工程]