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P.L.N. Ngo
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Cislunar space is emerging as a critical regime for future space missions. However, dedicated Space Situational Awareness (SSA) capabilities beyond Earth orbit remain limited. This thesis develops a simulation-based framework to design and assess space-based cislunar observers together with their sensor tasking strategies. Using the Earth-Moon Circular Restricted Three-Body Problem, representative catalogs of target and observer orbits are modeled, and an angles-only optical sensor with realistic exclusion constraints is simulated. Target states are estimated with an Extended Kalman Filter, while greedy schedulers based on information gain (IG), age-of-information, and finite-time Lyapunov exponent rewards are compared. The analysis shows that cislunar observers, particularly L2 halo orbits with IG tasking, dramatically outperform Earth-based sensors and reveal strong couplings between observational geometry and estimation accuracy. Age-of-information yields a simple, robust baseline, whereas the FTLE-based reward performs poorly in this formulation.
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Cislunar space is emerging as a critical regime for future space missions. However, dedicated Space Situational Awareness (SSA) capabilities beyond Earth orbit remain limited. This thesis develops a simulation-based framework to design and assess space-based cislunar observers together with their sensor tasking strategies. Using the Earth-Moon Circular Restricted Three-Body Problem, representative catalogs of target and observer orbits are modeled, and an angles-only optical sensor with realistic exclusion constraints is simulated. Target states are estimated with an Extended Kalman Filter, while greedy schedulers based on information gain (IG), age-of-information, and finite-time Lyapunov exponent rewards are compared. The analysis shows that cislunar observers, particularly L2 halo orbits with IG tasking, dramatically outperform Earth-based sensors and reveal strong couplings between observational geometry and estimation accuracy. Age-of-information yields a simple, robust baseline, whereas the FTLE-based reward performs poorly in this formulation.
Bachelor thesis
(2024)
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E.G.M. Abbenhuis, J. Agterdenbos, V. Bonanno, M. Camporeale, K. Do Cao, B.A. Kleipool, V.S. Lubbers, A.K. Mielczarek, T. Nakagawa, A.C. Petrache, R.N.H.W. van Gent, P.L.N. Ngo, S. Anand
The report details the design of a wildfire management system consisting of a swarm of electrically-powered unmanned aerial vehicles (UAVs) engaging in pre-, active- and post-fire operations. Specifically, the system monitors key parameters in wildfire detection and spread modelling, simultaneously providing a mobile communication network supporting emergency responders acting on the ground. At an altitude of 850m, necessary measurements can be taken with a three-meter ground resolution. The vehicles have a fixed-wing, single-propeller configuration, allowing a five-hour endurance. The swarm comprises twenty surveillance and five relay units, with five backup units stationed on the ground for contingency management. All necessary hardware for a swarm fits neatly into two standard twenty-foot shipping containers. After taking off from an electronically-activated deployable launch rail, the UAVs are capable of autonomous flight. The swarm intelligence is based on zig-zag flight patterns inside Voronoi sectors generated from wildfire risk maps dynamically updated by the UAVs' sensors. Ground operations are limited to monitoring the system state, as autonomous contingent behaviour is also accounted for. Assuming a maximum fire spread rate of 2.5 m/s, the system is capable of detection in 16 minutes on average. This is a competitive performance compared to existing fire detection methods such as satellites and aeroplanes. After flying, the UAVs return to the ground station and land autonomously using an arresting gear, removing the need for runways and landing gear. A financial analysis of the system reveals a cost of 750,000 USD per swarm, proving its competitiveness in price and performance compared to available market options. It is concluded that such a system is technically and financially feasible and can realistically impart a positive change to wildfire management efforts worldwide.
...
The report details the design of a wildfire management system consisting of a swarm of electrically-powered unmanned aerial vehicles (UAVs) engaging in pre-, active- and post-fire operations. Specifically, the system monitors key parameters in wildfire detection and spread modelling, simultaneously providing a mobile communication network supporting emergency responders acting on the ground. At an altitude of 850m, necessary measurements can be taken with a three-meter ground resolution. The vehicles have a fixed-wing, single-propeller configuration, allowing a five-hour endurance. The swarm comprises twenty surveillance and five relay units, with five backup units stationed on the ground for contingency management. All necessary hardware for a swarm fits neatly into two standard twenty-foot shipping containers. After taking off from an electronically-activated deployable launch rail, the UAVs are capable of autonomous flight. The swarm intelligence is based on zig-zag flight patterns inside Voronoi sectors generated from wildfire risk maps dynamically updated by the UAVs' sensors. Ground operations are limited to monitoring the system state, as autonomous contingent behaviour is also accounted for. Assuming a maximum fire spread rate of 2.5 m/s, the system is capable of detection in 16 minutes on average. This is a competitive performance compared to existing fire detection methods such as satellites and aeroplanes. After flying, the UAVs return to the ground station and land autonomously using an arresting gear, removing the need for runways and landing gear. A financial analysis of the system reveals a cost of 750,000 USD per swarm, proving its competitiveness in price and performance compared to available market options. It is concluded that such a system is technically and financially feasible and can realistically impart a positive change to wildfire management efforts worldwide.