A comparative analysis of algorithms for satellite operations scheduling

Scheduling is employed in everyday life, ranging from meetings to manufacturing and operations among other activities. One instance of scheduling in a complex real-life setting is space mission operations scheduling, i.e. instructing a satellite to perform fitting tasks during predefined time periods with a varied frequency to achieve its mission goals. Mission operations scheduling is pivotal to the success of any space mission, choreographing every task carefully, accounting for technological and environmental limitations and constraints along with mission goals.;It remains standard practice to this day, to generate operations schedules manually ,i.e. to collect requirements from individual stakeholders, collate them into a timeline, compare against feasibility and available satellite resources, and find potential conflicts. Conflict resolution is done by hand, checked by a simulator and uplinked to the satellite weekly. This process is time consuming, bears risks and can be considered sub-optimal.;A pertinent question arises: can we automate the process of satellite mission operations scheduling? And if we can, what method should be used to generate the schedules? In an attempt to address this question, a comparison of algorithms was deemed suitable in order to explore their suitability for this particular application.;The problem of mission operations scheduling was initially studied through literature and numerous interviews with experts. A framework was developed to approximate a generic Low Earth Orbit satellite, its environment and its mission requirements. Optimisation algorithms were chosen from different categories such as single-point stochastic without memory (Simulated Annealing, Random Search), multi-point stochastic with memory (Genetic Algorithm, Ant Colony System, Differential Evolution) and were run both with and without Local Search.;The aforementioned algorithmic set was initially tuned using a single 89-minute Low Earth Orbit of a scientific mission to Mars. It was then applied to scheduling operations during one high altitude Low Earth Orbit (2.4hrs) of an experimental mission.;It was then applied to a realistic test-case inspired by the European Space Agency PROBA-2 mission, comprising a 1 day schedule and subsequently a 7 day schedule - equal to a Short Term Plan as defined by the European Space Agency.;The schedule fitness - corresponding to the Hamming distance between mission requirements and generated schedule - are presented along with the execution time of each run. Algorithmic performance is discussed and put at the disposal of mission operations experts for consideration.Scheduling is employed in everyday life, ranging from meetings to manufacturing and operations among other activities. One instance of scheduling in a complex real-life setting is space mission operations scheduling, i.e. instructing a satellite to perform fitting tasks during predefined time periods with a varied frequency to achieve its mission goals. Mission operations scheduling is pivotal to the success of any space mission, choreographing every task carefully, accounting for technological and environmental limitations and constraints along with mission goals.;It remains standard practice to this day, to generate operations schedules manually ,i.e. to collect requirements from individual stakeholders, collate them into a timeline, compare against feasibility and available satellite resources, and find potential conflicts. Conflict resolution is done by hand, checked by a simulator and uplinked to the satellite weekly. This process is time consuming, bears risks and can be considered sub-optimal.;A pertinent question arises: can we automate the process of satellite mission operations scheduling? And if we can, what method should be used to generate the schedules? In an attempt to address this question, a comparison of algorithms was deemed suitable in order to explore their suitability for this particular application.;The problem of mission operations scheduling was initially studied through literature and numerous interviews with experts. A framework was developed to approximate a generic Low Earth Orbit satellite, its environment and its mission requirements. Optimisation algorithms were chosen from different categories such as single-point stochastic without memory (Simulated Annealing, Random Search), multi-point stochastic with memory (Genetic Algorithm, Ant Colony System, Differential Evolution) and were run both with and without Local Search.;The aforementioned algorithmic set was initially tuned using a single 89-minute Low Earth Orbit of a scientific mission to Mars. It was then applied to scheduling operations during one high altitude Low Earth Orbit (2.4hrs) of an experimental mission.;It was then applied to a realistic test-case inspired by the European Space Agency PROBA-2 mission, comprising a 1 day schedule and subsequently a 7 day schedule - equal to a Short Term Plan as defined by the European Space Agency.;The schedule fitness - corresponding to the Hamming distance between mission requirements and generated schedule - are presented along with the execution time of each run. Algorithmic performance is discussed and put at the disposal of mission operations experts for consideration

Methodology platform for prediction of damage events for self-sensing aerospace panels subjected to real loading conditions

With the growing size of aircraft fleets and the complexity of aircraft structures it has been proposed that there are many cost and operational benefits of installing a structural health monitoring system to monitor the aircraft’s structure throughout its in-service life. A method of achieving this is through monitoring the acoustic emission emitted during a damage event. One of the limiting factors to this however is having sufficient confidence in the placement of the sensors to ensure coverage while limiting the mass associated with the system. A series of five studies were conducted which use both experimental and numerical approaches to investigate Lamb wave propagation and its interaction with damage in both metallic and composite materials. These studies have used some of this data and through the use of genetic algorithms sought to optimise the placement of sensors with the objective of achieving a high probability of damage detection. The use of 3D scanning laser vibrometry has been harnessed along with the use of numerical reasoning using the local interaction simulation approach. This has enabled studies to be conducted which consider both the in-plane and out-of-plane components of the Lamb waves which is an important consideration when selected the appropriate sensing methods. In addition, a novel method of training sensor networks for AE location using the delta-t technique is also presented. The results of these studies has led to the development of two separate methodologies; one for the placement of sensors in an acousto-ultrasonic system for the detection of adhesive disbonds and one for the placement of AE sensors to maximise the coverage of the sensor network on a structure with complex geometry. These methodologies have many advantages, particular in their prompt convergence which makes progress towards enabling a concurrent sensor network-structure development

In pursuit of autonomous distributed satellite systems

Satellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global

In pursuit of autonomous distributed satellite systems

A la pàgina 265 diu: "In an effort to facilitate the reproduction of results, both the source code of the simulation environment and the configuration files that were prepared for the design characterisation are available in an open repository: https://github.com/carlesaraguz/aeossSatellite imagery has become an essential resource for environmental, humanitarian, and industrial endeavours. As a means to satisfy the requirements of new applications and user needs, novel Earth Observation (EO) systems are exploring the suitability of Distributed Satellite Systems (DSS) in which multiple observation assets concurrently sense the Earth. Given the temporal and spatial resolution requirements of EO products, DSS are often envisioned as large-scale systems with multiple sensing capabilities operating in a networked manner. Enabled by the consolidation of small satellite platforms and fostered by the emerging capabilities of distributed systems, these new architectures pose multiple design and operational challenges. Two of them are the main pillars of this research, namely, the conception of decision-support tools to assist the architecting process of a DSS, and the design of autonomous operational frameworks based on decentralised, on-board decision-making. The first part of this dissertation addresses the architecting of heterogeneous, networked DSS architectures that hybridise small satellite platforms with traditional EO assets. We present a generic design-oriented optimisation framework based on tradespace exploration methodologies. The goals of this framework are twofold: to select the most optimal constellation design; and to facilitate the identification of design trends, unfeasible regions, and tensions among architectural attributes. Oftentimes in EO DSS, system requirements and stakeholder preferences are not only articulated through functional attributes (i.e. resolution, revisit time, etc.) or monetary constraints, but also through qualitative traits such as flexibility, evolvability, robustness, or resiliency, amongst others. In line with that, the architecting framework defines a single figure of merit that aggregates quantitative attributes and qualitative ones-the so-called ilities of a system. With that, designers can steer the design of DSS both in terms of performance or cost, and in terms of their high-level characteristics. The application of this optimisation framework has been illustrated in two timely use-cases identified in the context of the EU-funded ONION project: a system that measures ocean and ice parameters in Polar regions to facilitate weather forecast and off-shore operations; and a system that provides agricultural variables crucial for global management of water stress, crop state, and draughts. The analysis of architectural features facilitated a comprehensive understanding of the functional and operational characteristics of DSS. With that, this thesis continues to delve into the design of DSS by focusing on one particular functional trait: autonomy. The minimisation of human-operator intervention has been traditionally sought in other space systems and can be especially critical for large-scale, structurally dynamic, heterogeneous DSS. In DSS, autonomy is expected to cope with the likely inability to operate very large-scale systems in a centralised manner, to improve the science return, and to leverage many of their emerging capabilities (e.g. tolerance to failures, adaptability to changing structures and user needs, responsiveness). We propose an autonomous operational framework that provides decentralised decision-making capabilities to DSS by means of local reasoning and individual resource allocation, and satellite-to-satellite interactions. In contrast to previous works, the autonomous decision-making framework is evaluated in this dissertation for generic constellation designs the goal of which is to minimise global revisit times. As part of the characterisation of our solution, we stressed the implications that autonomous operations can have upon satellite platforms with stringent resource constraints (e.g. power, memory, communications capabilities) and evaluated the behaviour of the solution for a large-scale DSS composed of 117 CubeSat-like satellite units.La imatgeria per satèl·lit ha esdevingut un recurs essencial per assolir tasques ambientals, humanitàries o industrials. Per tal de satisfer els requeriments de les noves aplicacions i usuaris, els sistemes d’observació de la Terra (OT) estan explorant la idoneïtat dels Sistemes de Satèl·lit Distribuïts (SSD), on múltiples observatoris espacials mesuren el planeta simultàniament. Degut al les resolucions temporals i espacials requerides, els SSD sovint es conceben com sistemes de gran escala que operen en xarxa. Aquestes noves arquitectures promouen les capacitats emergents dels sistemes distribuïts i, tot i que són possibles gràcies a l’acceptació de les plataformes de satèl·lits petits, encara presenten molts reptes en quant al disseny i operacions. Dos d’ells són els pilars principals d’aquesta tesi, en concret, la concepció d’eines de suport a la presa de decisions pel disseny de SSD, i la definició d’operacions autònomes basades en gestió descentralitzada a bord dels satèl·lits. La primera part d’aquesta dissertació es centra en el disseny arquitectural de SSD heterogenis i en xarxa, imbricant tecnologies de petits satèl·lits amb actius tradicionals. Es presenta un entorn d’optimització orientat al disseny basat en metodologies d’exploració i comparació de solucions. Els objectius d’aquest entorn són: la selecció el disseny de constel·lació més òptim; i facilitar la identificació de tendències de disseny, regions d’incompatibilitat, i tensions entre atributs arquitecturals. Sovint en els SSD d’OT, els requeriments del sistema i l’expressió de prioritats no només s’articulen en quant als atributs funcionals o les restriccions monetàries, sinó també a través de les característiques qualitatives com la flexibilitat, l’evolucionabilitat, la robustesa, o la resiliència, entre d’altres. En línia amb això, l’entorn d’optimització defineix una única figura de mèrit que agrega rendiment, cost i atributs qualitatius. Així l’equip de disseny pot influir en les solucions del procés d’optimització tant en els aspectes quantitatius, com en les característiques dalt nivell. L’aplicació d’aquest entorn d’optimització s’il·lustra en dos casos d’ús actuals identificats en context del projecte europeu ONION: un sistema que mesura paràmetres de l’oceà i gel als pols per millorar la predicció meteorològica i les operacions marines; i un sistema que obté mesures agronòmiques vitals per la gestió global de l’aigua, l’estimació d’estat dels cultius, i la gestió de sequeres. L’anàlisi de propietats arquitecturals ha permès copsar de manera exhaustiva les característiques funcionals i operacionals d’aquests sistemes. Amb això, la tesi ha seguit aprofundint en el disseny de SSD centrant-se, particularment, en un tret funcional: l’autonomia. Minimitzar la intervenció de l’operador humà és comú en altres sistemes espacials i podria ser especialment crític pels SSD de gran escala, d’estructura dinàmica i heterogenis. En els SSD s’espera que l’autonomia solucioni la possible incapacitat d’operar sistemes de gran escala de forma centralitzada, que millori el retorn científic i que n’apuntali les seves propietats emergents (e.g. tolerància a errors, adaptabilitat a canvis estructural i de necessitats d’usuari, capacitat de resposta). Es proposa un sistema d’operacions autònomes que atorga la capacitat de gestionar els sistemes de forma descentralitzada, a través del raonament local, l’assignació individual de recursos, i les interaccions satèl·lit-a-satèl·lit. Al contrari que treballs anteriors, la presa de decisions autònoma s’avalua per constel·lacions que tenen com a objectius de missió la minimització del temps de revisita global.Postprint (published version

Novel deep learning architectures for marine and aquaculture applications

Alzayat Saleh's research was in the area of artificial intelligence and machine learning to autonomously recognise fish and their morphological features from digital images. Here he created new deep learning architectures that solved various computer vision problems specific to the marine and aquaculture context. He found that these techniques can facilitate aquaculture management and environmental protection. Fisheries and conservation agencies can use his results for better monitoring strategies and sustainable fishing practices

Cost efficient 5G heterogeneous base station deployment using meta-heuristics

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonOver the last two decades, the telecommunication industry has witnessed sustained growth in the number of mobile user devices driven by the introduction of data services, the take-off of the internet and smart user equipment. This growth, which is forecasted to continue, has continued to push the data transfer capacity requirement on mobile networks and has motivated research into the design of 5th generation (5G) mobile networks. A key concern in the design of 5G is the infrastructure and power consumption cost of the base station network which is expected to be significantly more advanced and dense than that of existing conventional mobile networks. This thesis presents an optimisation framework for the cost efficient design of 5G base station networks, based on the application of meta-heuristic algorithms. The presented optimisation framework is centred on the ability to exploit three key technologies of 5G, a heterogonous base station network with small-cells, multi-antenna spatial multiplexing MIMO and cell range extension. The framework includes mathematical integer programming models for supporting the decisions about the optimal base station topology in a 5G mobile network and provides a clear core for the application of meta-heuristics for optimising 5G base station deployment. The core optimisation framework includes the definition of solution encoding/decoding and fitness mechanisms. To increase power consumption awareness of base station network design, an independent base station deployment strategy has been presented and evaluated. Simulation results show that the strategy can improve base station network design power consumption by as much as 34%. The work in this thesis has been extensively evaluated using a simulated 5G mobile network system model. Evaluations of algorithms have been performed through empirical measurements. The main contribution of this thesis is the definition of a clear framework for application fitness based heuristic search in the design of 5G mobile networks