Outlier Rejection on Payload Metadata System Time of LAPAN-A3 Satellite using Sequential RANSAC

2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES) Pub Date : 2022-11-24 DOI:10.1109/ICARES56907.2022.9993607

S. Utama, Chusnul Tri Judianto, Suraduita Mupasanta, Wakhid Abdurrokhman, Nur Salma Yusuf Hasanah, A. A. Qadir, Khairunnisa, P. R. Hakim

{"title":"Outlier Rejection on Payload Metadata System Time of LAPAN-A3 Satellite using Sequential RANSAC","authors":"S. Utama, Chusnul Tri Judianto, Suraduita Mupasanta, Wakhid Abdurrokhman, Nur Salma Yusuf Hasanah, A. A. Qadir, Khairunnisa, P. R. Hakim","doi":"10.1109/ICARES56907.2022.9993607","DOIUrl":null,"url":null,"abstract":"System time is one of the most pivotal metadata of a satellite payload, thus having outliers on the system time can lead to failure in the data processing. Therefore, an outlier rejection method is crucial to cleanse the metadata before partaking in further processes. In this research, three variants of the random sampling consensus (RANSAC) algorithm are selected to deal with outliers in the system time of the LAPAN-A3 satellite. Default RANSAC, RANSAC with least square, and RANSAC with median value are chosen to be tested to the synthetic data with a variation on the outlier ratio and standard deviation. RANSAC with the least square variant shows superiority in precision, recall, and robustness. Furthermore, a sequential RANSAC is built to deal with multiple structures on the metadata of LAPAN-A3. The method can estimate the outlier with a precision of 0.9 and a recall of 0.6.","PeriodicalId":252801,"journal":{"name":"2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)","volume":"279 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARES56907.2022.9993607","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

System time is one of the most pivotal metadata of a satellite payload, thus having outliers on the system time can lead to failure in the data processing. Therefore, an outlier rejection method is crucial to cleanse the metadata before partaking in further processes. In this research, three variants of the random sampling consensus (RANSAC) algorithm are selected to deal with outliers in the system time of the LAPAN-A3 satellite. Default RANSAC, RANSAC with least square, and RANSAC with median value are chosen to be tested to the synthetic data with a variation on the outlier ratio and standard deviation. RANSAC with the least square variant shows superiority in precision, recall, and robustness. Furthermore, a sequential RANSAC is built to deal with multiple structures on the metadata of LAPAN-A3. The method can estimate the outlier with a precision of 0.9 and a recall of 0.6.

查看原文本刊更多论文

基于序列RANSAC的LAPAN-A3卫星有效载荷元数据系统时间异常抑制

系统时间是卫星有效载荷中最关键的元数据之一，因此系统时间上的异常值可能导致数据处理失败。因此，在参与进一步的处理之前，异常值拒绝方法对于清理元数据至关重要。在本研究中，选择随机抽样一致性(RANSAC)算法的三种变体来处理LAPAN-A3卫星系统时间的异常值。选择默认RANSAC、最小二乘RANSAC和中位数RANSAC对异常值比和标准差变化的合成数据进行检验。具有最小二乘变体的RANSAC在查全率、查全率和鲁棒性方面具有优势。在此基础上，建立了一个序列RANSAC来处理lpan - a3元数据上的多个结构。该方法估计离群值的精度为0.9，召回率为0.6。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2022 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)

自引率

0.00%

发文量