Future Space Data, Missions and Sensors for CBRN Event Detection and Monitoring

Lead Research Organisation: University of Bristol
Department Name: Aerospace Engineering

Abstract

Future Chemical-Biological-Radiological-Nuclear-Explosive (CBRNe) threats could include a chemical explosion at a plant, a use of a nerve agent in an urban environment or a radioactive leak from a facility. As these threats come to the forefront of modern security and threat management interests, there is a present need to improve detection and modelling of these scenarios. The use of satellites has great potential to make contributions to future imaging and models, presenting opportunities for research and development.
The European Space Agency has requested studies into the use of space-based services to support CBRN(e) operations. Thales Alenia Space (TAS) has been working with a local SME, 'Riskaware', on this European Space Agency contract to look at information management systems for first responders to CBRN threats. These systems could improve the situational awareness of first responders in a CBRN scenario, allowing them to make better tactical decisions with more accurate and detailed information, potentially saving lives. The development of satellite technology to provide data to support these models could provide a better resolution and timeliness than is currently available. Among the technologies that could improve the quality of data are ideas such as Very Low Earth Orbit (VLEO) satellites along with LiDARs and hyperspectral imagers mounted on microsatellites, which have not previously been used on satellites of this type.
Initial analysis of potentially relevant available satellite data by the author indicates that there are several gaps, including high-resolution wind field data, and chemical, radiological, and biological detection. Many of these present opportunities for future missions which would be of benefit to the UK's space industry.
This PhD sits in the EPSRC Sensors and Engineering Design research areas.
The objectives of the PhD are:
To review currently available data for CBRN to ascertain gaps in data required
To review Earth observation instruments which could be used for CBRN
To review possible proxies which could help with gaps in CBRN data
To investigate the platforms and configuration necessary to accommodate the above Earth observation instruments
To investigate possible instruments that can be used on identified platforms, e.g. LIDAR on a VLEO satellite or LEO microsatellite
To provide analysis of any adaptations necessary to the payload or the platform.
The technical approach to the research is:
1. Literature review/survey of current technologies
2. Identification of gaps in knowledge and current and future instruments
3. Identification of possible approaches
4. Consideration of possible proxies
5. Integration of instruments on existing or future space platforms
6. Mission analysis calculations
7. Possible design of future sensor
8. Possible design of future platform to accommodate sensor

There are some technological challenges associated with this research, including that possible instruments such as LiDARs and hyperspectral imagers are large and heavy, and so will require miniaturization for use on potential platforms such as microsatellites. Additionally, these instruments need lower orbits to maximise resolution, but platforms such as VLEO require drag compensation to stay in orbit. These are all issues that must be addressed when discussing future technologies to gather data for CBRN applications. The novelty of the research and the approach lies in the use of space-based data, which does not see much use in the CBRN modelling field beyond visual terrain data, and in the definition of an instrument capable of providing this data, with the need to accommodate it to a novel platform such as VLEO or a microsatellite.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/T51763X/1 30/09/2019 07/11/2025
2286823 Studentship EP/T51763X/1 30/09/2019 29/09/2023 Gary Sutlieff