{"title":"Relative Navigation Methods for a Multi-Agent, On-Orbit Inspection Mission","authors":"Mark Mercier, D. Curtis","doi":"10.1109/PLANS53410.2023.10140084","DOIUrl":null,"url":null,"abstract":"On-orbit inspection is often a necessary prerequisite to satellite operations such as servicing and debris removal. In particular, multiple inspectors collaborating to inspect an unknown object can result in a faster and more comprehensive inspection. The contribution of this research is to provide a reliable, computationally efficient estimate for the position of each agent relative to a target in a multi-agent inspection. First, an overview of the problem dynamics, background, and methods used to build and solve a factor graph-based estimation technique is provided. Through the implementation of a Sliding Window (SW) filter, a factor graph can be applied to long duration scenarios while reducing processing requirements for estimation. An example scenario of three agents attempting to conduct an inspection while susceptible to a Sun exclusion zone that nulls some measurement information is prescribed. Development continues by comparing results for the developed Sliding Window Factor Graph (SWFG) against two extreme SW sizes of interest: an iterative Kalman filter (SW size = 1) and a full factor graph (SW size ≥ scenario duration). Results reveal the impact of both the Sun exclusion zone and sliding window size on estimation quality and computation time.","PeriodicalId":344794,"journal":{"name":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PLANS53410.2023.10140084","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
On-orbit inspection is often a necessary prerequisite to satellite operations such as servicing and debris removal. In particular, multiple inspectors collaborating to inspect an unknown object can result in a faster and more comprehensive inspection. The contribution of this research is to provide a reliable, computationally efficient estimate for the position of each agent relative to a target in a multi-agent inspection. First, an overview of the problem dynamics, background, and methods used to build and solve a factor graph-based estimation technique is provided. Through the implementation of a Sliding Window (SW) filter, a factor graph can be applied to long duration scenarios while reducing processing requirements for estimation. An example scenario of three agents attempting to conduct an inspection while susceptible to a Sun exclusion zone that nulls some measurement information is prescribed. Development continues by comparing results for the developed Sliding Window Factor Graph (SWFG) against two extreme SW sizes of interest: an iterative Kalman filter (SW size = 1) and a full factor graph (SW size ≥ scenario duration). Results reveal the impact of both the Sun exclusion zone and sliding window size on estimation quality and computation time.