PhD student presentations Seminar
- Time:
- 14:00
- Date:
- 4 December 2012
- Venue:
- Room 3001, building 34
For more information regarding this seminar, please telephone Camilla Colombo on +44 (0)23 8059 2319 or email C.Colombo@soton.ac.uk .
Event details
An Astro group seminar
Simon George "Simulations of SAR Ocean Turbulence Signatures"
Synthetic Aperture Radar (SAR) has shown remarkable ability to resolve the surface signatures of turbulent phenomena such as eddies, breaking waves and ship wakes in the ocean. Turbulence generated by a moving surface vessel's wake was simulated using CFD and translated to simulated SAR imagery through use of an integrated ocean-electromagnetic wave interaction model. This work revolves around the examination of surface signatures for a range of ocean and instrument configurations and analysis of simulated remote-sensing signatures for the ability to resolve turbulent structure from the resulting imagery. This can improve understanding of the relationships between small-scale turbulence and radar backscattering, and derive beneficial instrument parameters for maximising these observations. The results obtained indicate that turbulent structure embedded in ship wakes can be translated to and resolved by changes in radar backscatter.
Warin Kiadtikornthaweeyot "Adaptive image compression for CubeSats"
This research proposes an alternative image processing system for CubeSats, based on automatic region of interest detection and image compression techniques. Many CubeSats have been used for earth observation using various imaging devices, which produce large amounts of data, and the increased resolution that is expected in the near future will lead to further increases in data and thus the requirement for larger storage space and faster download rates. The limitations of bandwidth transmission, power and storage on-board are significant issues in the design of CubeSats and restrict the transmission of data to the ground station. This research discusses the design of an adaptive on-board image processing algorithm for payloads on CubeSats. The proposed algorithm consists of the Region of interest (ROI) automatic detection and the image compression module. The ROI is a technique that defines the area of an image that contains useful information and removes the unwanted areas. The edge, histogram and texture segmentation techniques are implemented in the proposed algorithm. The image compression module implemented image compression recommendation, which is based on discrete wavelet transforms. The proposed system performs the ROI automatic detection first then the data pass though the image compression. The preliminary result shows that the proposed algorithm be able to reduce the size of the satellite image.
Ben Schwarz "Fractionated Satellites"
The concept of fractionated satellites involves the decomposition of the traditional monolithic satellite into a system of free flying satellites with specific functions, such as to provide a high speed data relay to the ground. These satellites share resources to achieve the mission. To date, research into fractionated satellites has largely focused on quantifying the programmatic and economic benefits of implementing this concept for the next generation of space systems. However the significant technical and operational challenges to satellite fractionation have not been studied as extensively. This paper examines the many different configurations a fractionated satellite might take and how they might be operated once in space. A variety of fractionated satellite architectures have been simulated taking into account the satellite and subsystem failures based upon a failure rate curve. The architectures are characterised by parameters, such as the degree to which the system is fractionated, the number of satellites in the system, and the distribution of subsystems on the satellites. There are a very large number of combinations and so simulations have been performed to identify the optimum architecture over a long period of continuous operation. The objective of these simulations is to characterise how each fractionated architecture performs over a 50 year lifetime with respect to the failures. Each architecture is assessed with respect to two traits: the percentage of the lifetime that the payload and system operations can be maintained, and the total mass launched. A local search optimisation based on this assessment is used to highlight particular characteristics of fractionated architectures that maximise operational time whilst minimising the mass. Results show that the outcome of this optimisation will be strongly influenced by the redundancy strategy employed, the distribution of subsystems throughout the fractionated system and the degree of fractionation of the system.
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Speaker information
Simon George ,PhD student with the Astro group
Warin Kiadtikornthaweeyot ,PhD student with the Astro group
Ben Schwarz ,PhD student with the Astro group