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Multi-Target Tracking Algorithms for the Evolving Space Object Population
Multi-Target Tracking Algorithms for the Evolving Space Object Population
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260311091550.5
- ISBN
- 9798270229184
- DDC
- 629.41
- 서명/저자
- Multi-Target Tracking Algorithms for the Evolving Space Object Population / Benjamin Louis Reifler
- 발행사항
- [Sl] : The University of Texas at Austin, 2025
- 형태사항
- 1 electronic resource (138 pages)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-06, Section: B.
- 주기사항
- Advisors: Jones, Brandon A. Committee members: Humphreys, Todd E.; Akella, Maruthi R.; Coder, Ryan D.; Jah, Moriba.
- 학위논문주기
- - Ph.D. : The University of Texas at Austin, 2025.
- 초록/해제
- 요약The population of objects orbiting the Earth is growing rapidly, increasing the risk of catastrophic collision events and the demand on existing systems for space situational awareness (SSA). Much of this growth is being driven by the construction of proliferated low Earth orbit (PLEO) satellite constellations for global internet connectivity. This dissertation addresses some of the challenges that must be overcome to develop an SSA system that can handle this evolving population. This work focuses on the multi-target tracking (MTT) algorithms that process measurements from sensors to estimate the orbits of objects in space. We derive the field-of-view-partitioned generalized labeled multi-Bernoulli filter (FP-GLMBF), a multiple hypothesis multi-target filter designed for use with sensor networks with limited fields of view (FOVs) and demonstrate how its useful features can be applied to other MTT algorithms to improve their limited-FOV tracking performance. We then apply the FP-GLMBF to a simulated SSA scenario that includes a new PLEO constellation and assess its performance in terms of computation time, memory usage, and tracking accuracy. Finally, we derive a method for initial orbit determination (IOD) that enables a multi-target filter to quickly attribute and acquire custody of a newly detected space object that is produced by a tracked object. Our IOD algorithm is applied to simulated breakup and satellite deployment scenarios to demonstrate its effectiveness.
- 언어주기
- English
- 일반주제명
- Astrophysics
- 일반주제명
- Astronomy
- 키워드
- Multi-traget
- 키워드
- Tracking
- 기타저자
- The University of Texas at Austin Aerospace Engineering
- 기본자료저록
- Dissertations Abstracts International. 87-06B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520260311091550.5
■006m o d
■007cr|nu||||||||
■020 ▼a9798270229184
■040 ▼aMiAaPQD▼beng▼cMiAaPQD▼erda
■082 ▼a629.41
■1001 ▼aReifler, Benjamin Louis▼eauthor.
■24510▼aMulti-Target Tracking Algorithms for the Evolving Space Object Population ▼cBenjamin Louis Reifler
■260 ▼a[Sl]▼bThe University of Texas at Austin▼c2025
■264 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a1 electronic resource (138 pages)
■336 ▼atext▼btxt▼2rdacontent
■337 ▼acomputer▼bc▼2rdamedia
■338 ▼aonline resource▼bcr▼2rdacarrier
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-06, Section: B.
■500 ▼aAdvisors: Jones, Brandon A. Committee members: Humphreys, Todd E.; Akella, Maruthi R.; Coder, Ryan D.; Jah, Moriba.
■5021 ▼bPh.D.▼cThe University of Texas at Austin▼d2025.
■520 ▼aThe population of objects orbiting the Earth is growing rapidly, increasing the risk of catastrophic collision events and the demand on existing systems for space situational awareness (SSA). Much of this growth is being driven by the construction of proliferated low Earth orbit (PLEO) satellite constellations for global internet connectivity. This dissertation addresses some of the challenges that must be overcome to develop an SSA system that can handle this evolving population. This work focuses on the multi-target tracking (MTT) algorithms that process measurements from sensors to estimate the orbits of objects in space. We derive the field-of-view-partitioned generalized labeled multi-Bernoulli filter (FP-GLMBF), a multiple hypothesis multi-target filter designed for use with sensor networks with limited fields of view (FOVs) and demonstrate how its useful features can be applied to other MTT algorithms to improve their limited-FOV tracking performance. We then apply the FP-GLMBF to a simulated SSA scenario that includes a new PLEO constellation and assess its performance in terms of computation time, memory usage, and tracking accuracy. Finally, we derive a method for initial orbit determination (IOD) that enables a multi-target filter to quickly attribute and acquire custody of a newly detected space object that is produced by a tracked object. Our IOD algorithm is applied to simulated breakup and satellite deployment scenarios to demonstrate its effectiveness.
■546 ▼aEnglish
■590 ▼aSchool code: 0227
■650 4▼aAstrophysics
■650 4▼aAstronomy
■653 ▼aMulti-traget
■653 ▼aTracking
■653 ▼aSpace situational awareness
■653 ▼aInitial orbit determination
■7102 ▼aThe University of Texas at Austin▼bAerospace Engineering.▼edegree granting institution.
■7201 ▼aJones, Brandon A.▼edegree supervisor.
■7730 ▼tDissertations Abstracts International▼g87-06B.
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17361142▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
