A critical component within any SST system is the data processing chain, having as input data provided by a sensor (such as a telescope or a radar) and as main output orbit determination (OD) on which rely many services (object identification, collision avoidance, atmospheric re-entry, fragmentation, etc.). This is a huge field of research and technology development at international level addressing space infrastructure preservation. The project scope is to setup and test an original prototype of a real time data processing tool for automatic LEO space objects detection and their position determination having as input images provided by a very wide field of view (FOV) robotic optical SST instrument.

  • The proposed data processing tool will contain a computing board and a software package both of them developed by Technical University of Cluj-Napoca (TUCN), as described later in this proposal.
  • BITNET CCSS (BITNET, partner in this proposal) will integrate the data processing tool developed by TUCN into one of its SST optical sensors and will test/validate the data provided by the data processing tool.
The end outcome of this project is to contribute to the development of a NEW robotic sensor which can be integrated in the European SST network, especially for providing data for re-entry services.


From the Technical University of Cluj-Napoca, the project coordinator, the following key persons:

The industrial partner of the project, BITNET CCSS, the following key members:

  • Octavian Cristea - researcher/physicist
  • Dr. Paul Dolea
  • Dr. Vlad Paul Dascal


The workplan of the project is organized in three phases, corresponding to the calendar years covered.

Phase 1: May 2020 – December 2020.

  1. Definition of the LEO detection system architecture Definition of sensor architecture, the main processing chain for the image processing and object detection architecture, starting from the existing algorithms and the requirements for SST processing systems.
  2. Definition of the testing and validation system architecture Definition of the observation system/sensor architecture and SST observation strategy which will be used for testing and validation, based on its own available resources. Preliminary observations for data collection will be also carried out, to be used during the system development.
  3. Development of the image processing and object detection software package– phase 1 The image processing algorithms will be optimized for accuracy and speed, and integrated in a complete processing package, able to deliver object detection results in the formats required by the SST systems.

Phase 2: January 2021 – December 2021.

  1. Development of the image processing and object detection software package– phase 2 This activity will continue A1.3, further optimizing the image processing algorithms, and adapting them for the dedicated hardware architecture of the observation station.
  2. Development of the interfacing components between the observation systems and the image processing system The partners will work together to develop the hardware and the software components for interfacing the optics and the camera with the image processing computing architecture, including image data transfer interfaces, commands for the optics orientation, and timing.
  3. Development of the remote control application for observation coordination The application that will connect to the observation stations for control and data retrieval will be developed mainly by TUCN, with assistance from BITNET. This application will also include star data retrieval from the available catalogs.
  4. Definition of the testing and validation methodology BITNET will define the methodology for testing and validation, including the observation strategies, the range of objects to be detected, the expected accuracy and response time.
  5. Integration of the SST image acquisition system and preliminary operation testing – phase 2 The partners will integrate the hardware and the software components of the acquisition system and perform fully automated acquisition of SST-like image sequences. The processing will not be yet fully complete, automated and real time, but parts of the processing software will be tested in the acquisition cycle.
  6. Dissemination of preliminary results The preliminary results will be disseminated as patent claims and scientific papers, which will constitute the deliverables for this activity (D16).

Phase 3: January 2022 – April 2022.

  1. Integration of the system components The partners will put everything together to create the final acquisition and processing system.
  2. Testing and validation through space objects observation campaigns Extensive observation sessions will be conducted by the partners and the sub-contractor to test, tune and finally validate and establish the operation parameters of the system.
  3. Results dissemination and employment The final results will be disseminated through journal articles and conference presentations (D17). Also, the partners will attempt to employ the resulted system in a European or worldwide SST effort.


The resulting publications will be linked here.


The project reports will be published here.

Phase 1 report.


Radu Danescu

Technical University of Cluj-Napoca
Computer Science Department,
Str. Memorandumului, Nr. 28, 400 114, Cluj Napoca

Office: Baritiu str. 26, room 37
Phone: +40 264 401457


Full project name:
CAMELEON - Compact image Acquisition and position MEasurement system for targets in the LEO raNge


Ministery of Research and Innovation, CNCS – UEFISCDI