Behaviour modelling of non-cooperative space objects and strategies for decision support in space situational awareness / (Record no. 433896)

MARC details
000 -LEADER
fixed length control field 05378nam a22003617a 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250801b |||||||| |||| 00| 0 eng d
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 629.435
Item number SHI
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Shivshankar, S
245 ## - TITLE STATEMENT
Title Behaviour modelling of non-cooperative space objects and strategies for decision support in space situational awareness /
Remainder of title by S.Shivshankar
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Bangalore :
Name of publisher, distributor, etc Indian Institute of Science,
Date of publication, distribution, etc 2025.
300 ## - PHYSICAL DESCRIPTION
Extent xviii, 204 p. :
Other physical details col. ill. ;
Accompanying material e-Thesis
Size of unit 43.13 Mb
500 ## - GENERAL NOTE
General note Includes bibliographical references
502 ## - DISSERTATION NOTE
Dissertation note PhD;2025;Aerospace Engineering
520 ## - SUMMARY, ETC.
Summary, etc Space Situational Awareness [SSA] is defined as the comprehensive knowledge of Resident Space Objects [RSO] which may include satellites, rocket bodies, debris etc. and the ability to understand their behaviour. SSA solutions should provide a quantifiable and timely technical evidence to the decision maker about the behavioural attributes of space domain threats, hazards and its implications. Space objects can be majorly categorized into two broad types, cooperative space objects and non-cooperative space objects. A non-cooperative space object is defined as a non-friendly object in space and can be perceived as a threat if it performs anomalous maneuvers in space. Modelling pattern-of-life of non-cooperative space objects is an essential requirement of SSA. Maneuvers of non-cooperative satellites is an important event of interest in their life pattern. In this thesis, we investigate the behaviour of various classes of satellites through data driven modelling. We also study the threat perception from non-cooperative space objects to space assets of our interest. There are four key areas, in which the thesis has significantly contributed. The first area deals with investigating, exploring and modelling pattern-of-life of non-cooperative space objects. We have crafted data-driven solution methodologies from time series analysis and machine learning to suit specific requirements. The second area pertains to segregating the maneuvers of non-cooperative space objects as there are numerous non-cooperative space objects and not all maneuvers of non-cooperative space objects may be threatening in nature. In this thesis, we designed an approach to segregate benign and regular pattern-of-life maneuvers of non-cooperative space objects from their orbital data . The routine pattern-of-life maneuvers of satellites are events of interest, but are infrequent and hence the non-maneuver class was observed to be far more numerous than the maneuver class label in the dataset. Through this thesis work, we have applied Synthetic Minority Oversampling Techniques (SMOTE) and its variants to handle the imbalance in dataset available for classification. Different missions of cooperative civilian satellites in Low Earth Orbit (LEO) space regime were evaluated to prove the efficacy of the approach. The third area of contribution is in developing methodologies to estimate the threat perception for Geostationary Orbit (GEO) space regime. Modelling pattern-of-life of non-cooperative GEO satellites helps to identify anomalous behaviour and is essential for SSA. Additionally, given a satellite of interest, an assessment of the area of influence of neighbourhood satellite operations is critical for assessment of threat. Nearest neighbour search is a fundamental problem in computational geometry and we studied two major concepts of computational geometry , the Voronoi diagram and the Delaunay triangulation in detail and devised algorithms to assess threat in the GEO space regime. The last area of contribution is with estimating the time when a satellite would maneuver and the parameters that influence the maneuver occurrence. This would support scheduling the limited and costly ground based sensors to monitor the large number of space objects. Conventional machine learning regression methods are not suited to be able to include both the event and time aspects as the outcome. Therefore, in this thesis, we devised a solution methodology by applying Time-to-Event data analysis (survival analysis) techniques to assess whether a satellite maneuvered, and also estimate when the next maneuver would occur. We have explored a variety of approaches from the gamut of survival analysis framework. Detailed experimental results based on real life satellite orbital datasets are presented to bring out the effectiveness of the solution methodology. To summarize, the thesis contributes by developing a space situational awareness system to achieve behavioural modelling, classification and characterization of space objects of interest, maneuver classification, anomaly detection and threat assessment through data driven methodologies.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Space situational awareness
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Space domain awareness
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Space security
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Space technology
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Resident space objects
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Maneuvers
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Space maneuvers
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Synthetic minority oversampling techniques
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element SMOTE
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Low earth orbit
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Geostationary orbit
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Behavioural modelling
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data driven methodologies
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Advised by Ghose, Debasish
Relator term Advisor
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://etd.iisc.ac.in/handle/2005/7006
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Thesis

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