Runbo Dong;Huadong Guo;Mengxiong Zhou;Hanlin Ye;Guang Liu
{"title":"Geolocation Uncertainty Analysis of Moon-Based Earth Observations","authors":"Runbo Dong;Huadong Guo;Mengxiong Zhou;Hanlin Ye;Guang Liu","doi":"10.1109/LGRS.2024.3500021","DOIUrl":null,"url":null,"abstract":"The geometric characteristics of Moon-based Earth observation platforms differ significantly from those of satellite platforms, with geolocation being a key factor that impacts data quality. The geolocation of a Moon-based sensor is influenced by three key factors: lunar ephemeris (lunar position and libration), Earth orientation parameters (EOPs), and the Earth reference model. Measurement errors from these three sources can significantly affect the geolocation accuracy of a Moon-based sensor. This study proposes a new unbiased estimation method to quantify the geolocation uncertainty introduced by these factors, based on the fusion of multiversion datasets. The method avoids making assumptions about the error distribution of ephemeris parameters while providing an effective approximation of the spatiotemporal patterns of geolocation uncertainty. We integrate three types of ephemeris data, three Earth reference models, and multiple EOPs datasets to assess the overall distribution of geolocation uncertainty and separately evaluate the geolocation uncertainty introduced by each individual factor using control variates method. The results indicate that the maximum total geolocation uncertainty caused by the three factors is about 46 m. Ephemeris errors are the dominant contributor, accounting for more than 98% of the total uncertainty. In addition, measurement errors in lunar libration also account for why longitudinal uncertainty is significantly greater than latitudinal uncertainty.","PeriodicalId":91017,"journal":{"name":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","volume":"22 ","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10755111/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The geometric characteristics of Moon-based Earth observation platforms differ significantly from those of satellite platforms, with geolocation being a key factor that impacts data quality. The geolocation of a Moon-based sensor is influenced by three key factors: lunar ephemeris (lunar position and libration), Earth orientation parameters (EOPs), and the Earth reference model. Measurement errors from these three sources can significantly affect the geolocation accuracy of a Moon-based sensor. This study proposes a new unbiased estimation method to quantify the geolocation uncertainty introduced by these factors, based on the fusion of multiversion datasets. The method avoids making assumptions about the error distribution of ephemeris parameters while providing an effective approximation of the spatiotemporal patterns of geolocation uncertainty. We integrate three types of ephemeris data, three Earth reference models, and multiple EOPs datasets to assess the overall distribution of geolocation uncertainty and separately evaluate the geolocation uncertainty introduced by each individual factor using control variates method. The results indicate that the maximum total geolocation uncertainty caused by the three factors is about 46 m. Ephemeris errors are the dominant contributor, accounting for more than 98% of the total uncertainty. In addition, measurement errors in lunar libration also account for why longitudinal uncertainty is significantly greater than latitudinal uncertainty.