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Identifying Identifying

Identifying - PowerPoint Presentation

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Uploaded On 2016-05-18

Identifying - PPT Presentation

NaK Objects in Space Debris Johanne Christensen Problem Soviet RORSAT satellites were deployed between 1967 to 1988 Some of the satellites had nuclear reactors The nuclear satellites were decommissioned in the 1980s by boosting the satellite to a graveyard orbit and jettisoning the reactor ID: 324442

objects data wavelength clusters data objects clusters wavelength inclination range satellites nak alt information satellite altitude decay correlation rorsat

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Slide1

Identifying NaK Objectsin Space Debris

Johanne ChristensenSlide2

ProblemSoviet RORSAT satellites were deployed between 1967 to 1988

Some of the satellites had nuclear reactors

The nuclear satellites were decommissioned in the 1980s by boosting the satellite to a graveyard orbit and jettisoning the reactor

NaK coolant was leaked due to a faulty seal in 16 satellitesCan we identify which groups of NaK objects originated from each satellite?

RORSATSlide3

Data1076 data objects with 10 attributes

Data comes from the MIT Haystack Radar in MA

75° Elevation East is examined

Haystack can only identify objects larger than 5mmData contains location information (alt, range, range-rate, inclination) and wavelength informationWavelength information gives the information on the composition of the object

Additional data about the RORSAT satellites (orbit heights and inclination) was also givenSlide4

PreprocessingCorrelated all the columns

Alt and Range have very high correlation >.99

High correlation among the wavelength data (PP, OP, RCS)

Low correlation between the location data and wavelength dataCan omit the wavelength dataTells us that the objects are all NaKSlide5

Clustering

Need to remove outliers, since they will skew the clusters

Used

DBScan and removed noise pointUsed visualization and removed a point with significantly higher rdot

K-means with 16 clustersAttributes Used: Alt, Inclination, Range-Rate

Inclination and Altitude by ClusterSlide6

Refining ClustersRunning the clustering algorithm produces several clusters with

centroids

under 800km

Does not match satellite dataMany of the objects are below 700km, while 15 of the satellites are orbiting at 900kmOrbital decay is likely – most of the low altitude objects are small (<1cm)Slide7

Refining ClustersRemoved objects at low altitude, below 700km

Clustered with K-means, 30 clusters

Inc and Alt Before and After Removing Low AltitudesSlide8

PostprocessingMerged similar clusters based on inclination and range-rate

Accounts for orbital decay, since objects decay at different ratesSlide9

Merged Clusters