Image and processing models for satellite detection in images acquired by Space-based Surveillance-of-Space sensors

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Authors
  1. Levesque, M.P.
Corporate Authors
Defence R&D Canada - Valcartier, Valcartier QUE (CAN)
Abstract
In the context of the surveillance of space, known resident space objects (RSO), i.e. active satellites and space debris, need to be acquired periodically to ensure that the knowledge of their orbital parameters is up-to-date. The most sensitive observation method consists of acquiring an image sequence while the target is actively tracked by the optical system such the RSO appears stationary in the image sequence. This generates an incredible amount of data which requires efficient detection algorithms and automated processing software. In this context, this document presents models for image formation, acquisition, and processing. From the observation request to the production of the images, the stream of events is briefly modeled. This ensures that a-priori knowledge and strategy will be applied to efficiently process the acquired data. These models produce a series of algorithms used to separate the image components and detect the RSO. This document presents algorithm diagrams that can be used to develop the processing software.

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Report Number
DRDC-VALCARTIER-TR-2009-095 — Technical Report
Date of publication
01 Sep 2010
Number of Pages
57
DSTKIM No
CA034305
CANDIS No
533801
Format(s):
Electronic Document(PDF)

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