Alessandro Gardi | Khalifa University (original) (raw)

Papers by Alessandro Gardi

Journal of Air Transport Management, 2021

Multi-airport systems are growing in number and size globally, despite being afflicted by known i... more Multi-airport systems are growing in number and size globally, despite being afflicted by known inefficiencies due to the interferences between the flows of neighbouring airports. A macroscopic empirical approach is proposed in this paper to estimate the capacity penalties and demonstrated by a numerical case study for Beijing, which is projected to become one of the busiest metroplexes in Asia. The Pareto envelopes of the theoretical and observed peak hour capacities are statistically analysed to quantify the penalties in a comparable metroplex and are subsequently modulated by a sigmoid correlation function. The analysis predicts the practical capacity of Daxing, the penalty incurred by the pre-existing Capital airport and by the total multi-airport system. Various findings are drawn and discussed, highlighting the needs for further research.

Computers, 2021

With increasingly higher levels of automation in aerospace decision support systems, it is impera... more With increasingly higher levels of automation in aerospace decision support systems, it is imperative that the human operator maintains the required level of situational awareness in different operational conditions and a central role in the decision-making process. While current aerospace systems and interfaces are limited in their adaptability, a Cognitive Human Machine System (CHMS) aims to perform dynamic, real-time system adaptation by estimating the cognitive states of the human operator. Nevertheless, to reliably drive system adaptation of current and emerging aerospace systems, there is a need to accurately and repeatably estimate cognitive states, particularly for Mental Workload (MWL), in real-time. As part of this study, two sessions were performed during a Multi Attribute Task Battery (MATB) scenario, including a session for offline calibration and validation and a session for online validation of eleven multimodal inference models of MWL. The multimodal inference model implemented included an Adaptive Neuro Fuzzy Inference System (ANFIS), which was used in different configurations to fuse data from an Electroencephalogram (EEG) model’s output, four eye activity features and a control input feature. The online validation of the ANFIS models produced good results, while the best performing model (containing all four eye activity features and the control input feature) showed an average Mean Absolute Error (MAE) = 0.67 ± 0.18 and Correlation Coefficient (CC) = 0.71 ± 0.15. The remaining six ANFIS models included data from the EEG model’s output, which had an offset discrepancy. This resulted in an equivalent offset for the online multimodal fusion. Nonetheless, the efficacy of these ANFIS models could be confirmed by the pairwise correlation with the task level, where one model demonstrated a CC = 0.77 ± 0.06, which was the highest among all of the ANFIS models tested. Hence, this study demonstrates the suitability for online multimodal fusion of features extracted from EEG signals, eye activity and control inputs to produce an accurate and repeatable inference of MWL.

Atmosphere, 2021

Atmospheric effects have a significant impact on the performance of airborne and space laser syst... more Atmospheric effects have a significant impact on the performance of airborne and space laser systems. Traditional models used to predict propagation effects rely heavily on simplified assumptions of the atmospheric properties and their interactions with laser systems. In the engineering domain, these models need to be continually improved in order to develop tools that can predict laser beam propagation with high accuracy and for a wide range of practical applications such as LIDAR (light detection and ranging), free-space optical communications, remote sensing, etc. The underlying causes of laser beam attenuation in the atmosphere are examined in this paper, with a focus on the dominant linear effects: absorption, scattering, turbulence, and non-linear thermal effects such as blooming, kinetic cooling, and bleaching. These phenomena are quantitatively analyzed, highlighting the implications of the various assumptions made in current modeling approaches. Absorption and scattering, as the dominant causes of attenuation, are generally well captured in existing models and tools, but the impacts of non-linear phenomena are typically not well described as they tend to be application specific. Atmospheric radiative transfer codes, such as MODTRAN, ARTS, etc., and the associated spectral databases, such as HITRAN, are the existing tools that implement state-of-the-art models to quantify the total propagative effects on laser systems. These tools are widely used to analyze system performance, both for design and test/evaluation purposes. However, present day atmospheric radiative transfer codes make several assumptions that reduce accuracy in favor of faster processing. In this paper, the atmospheric radiative transfer models are reviewed highlighting the associated methodologies, assumptions, and limitations. Empirical models are found to offer a robust analysis of atmospheric propagation, which is particularly well-suited for design, development, test and evaluation (DDT&E) purposes. As such, empirical, semi-empirical, and ensemble methodologies are recommended to complement and augment the existing atmospheric radiative transfer codes. There is scope to evolve the numerical codes and empirical approaches to better suit aerospace applications, where fast analysis is required over a range of slant paths, incidence angles, altitudes, and atmospheric conditions, which are not exhaustively captured in current performance assessment methods.

Progress in Aerospace Sciences, 2019

Progress in spaceflight research has led to the introduction of various manned and unmanned reusa... more Progress in spaceflight research has led to the introduction of various manned and unmanned reusable space vehicle concepts, opening up uncharted opportunities for the newborn space transport industry. For future space transport operations to be technically and commercially viable, it is critical that an acceptable level of safety is provided, requiring the development of novel mission planning and decision support tools that utilize advanced Communication, Navigation and Surveillance (CNS) technologies, and allowing a seamless integration of space operations in the current Air Traffic Management (ATM) network. A review of emerging platform operational concepts is conducted, highlighting both the challenges and the opportunities brought in by the integration with conventional atmospheric air transport. Common launch and re-entry planning methodologies are then discussed, where the physical and computational limitations of these approaches are identified and applicability to future commercial space transport operations is assessed. Attention is then turned to the on-orbit phase, where the unique hazards of the space environment are examined, followed by an overview to the necessary elements required for space object de-confliction and collision avoidance modelling. The regulatory framework evolutions required for spacecraft operations are then discussed, with a focus on space debris mitigation strategies and operational risk assessment. Within the atmospheric domain, possible extensions and alternatives to the conventional airspace segregation approaches are identified including promising Air Traffic Flow Management (ATFM) techniques to facilitate the integration of new-entrant platforms. Lastly, recent modelling approaches to meet on-orbit risk criteria are discussed and evolutionary requirements to improve current operational procedures are identified. These insights will inform future research on CNS/ATM and Avionics (CNS + A) systems and associated cyber-physical architectures for Space Traffic Management (STM).

AIAA Guidance, Navigation and Control Conference (Scitech 2019), 2019

This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on ... more This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on performance modeling and the system layout. Acoustic transmitters are arranged at known fixed locations and broadcast their respective signals following a Time Division Multiple Access (TDMA) scheme. The receiver position is calculated based on Time of Arrival (TOA) based ranging measurements from a minimum of four transmitters. The transmitters are arranged optimally to minimize Position Dilution of Precision (PDOP) as well as maximizing sensor availability. The proposed technique can provide accurate navigation observables in indoor environments, where conventional satellite-based navigation systems cannot deliver the required Position, Velocity, and Time (PVT) data. Additionally, being based on acoustic signals, it is immune to signal-in-space electromagnetic interferences. The TDMA based acoustic navigation system is described, with potential errors in ranging due to Doppler effect, multipath, atmospheric propagation, and signal delays. The error in positioning due to platform dynamics is also discussed. This analysis will lead to an optimized arrangement of transmitters supporting the future ground and flight experimental activities.

Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil, 2018

Unmanned Aircraft Systems (UAS), also known as drones, are capable of autonomously carrying out a... more Unmanned Aircraft Systems (UAS), also known as drones, are capable of autonomously carrying out an increasing number of duties with substantially greater efficiency compared to human intervention. UAS researchers aim to enhance the levels of safety, mission effectiveness and autonomy, as well as explore additional capabilities. Crop health monitoring is a very promising application of UAS as the early detection of plant diseases can supplement traditional crop monitoring techniques (such as visual observation) to support timely mitigation, thereby offering substantial benefits to crop yield and quality. This paper presents new UAS-borne Electro-Optics/Infrared (EO/IR) systems based on bistatic Light Detection and Ranging (LIDAR) for early detection of crop diseases. The proposed bistatic LIDAR system measures over extended observation periods above the crop canopy anomalies in carbon dioxide (CO 2) concentration potentially associated with disruptions in the plant photosynthesis. In particular, this paper discusses the application of the bistatic LIDAR to the early detection of powdery mildew in strawberry crops and presents the initial modelling and simulation activities performed to predict the sensor performance. Based on the results of this analysis, a plan for future experimental activities is also developed.

Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil, 2018

The steadily increasing air traffic demand has highlighted a need to evolve existing Air Traffic ... more The steadily increasing air traffic demand has highlighted a need to evolve existing Air Traffic Flow Management (ATFM) methodologies by increasing automation support in airborne and ground-based systems and more flexible modulation of air traffic controller workload. Dynamic Airspace Management (DAM) aims at optimising the demand-capacity balance in all airspace regions at all times with a particular focus on capacity modulation measures. In this paper, we propose a novel DAM approach supporting the dynamic morphing of airspace sector boundaries based on an optimal-control formulation. The Eulerian continuity principle is used to model the air traffic flow at a macroscopic scale and workload-based capacity constraints are considered to determine the optimal variations in sector volumes. The demand levels are determined and the traffic flow theory based on the principle of continuity is used to propagate the demand across airspace sectors, approximated as 2D polygons. The newly developed sector morphing framework will be integrated into next-generation ATFM decision support systems to drive adaptive human-machine interfaces and interactions supporting more efficient exploitation of airspace resources.

Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil, 2018

Unmanned Aircraft Systems (UAS) offer many opportunities in a wide range of industries to support... more Unmanned Aircraft Systems (UAS) offer many opportunities in a wide range of industries to support remote sensing and surveillance. While platform autonomy and intelligence have seen large advances in recent decades, a key challenge is the operation of multiple Unmanned Aerial Vehicles (UAV) by a single operator in 'one-to-many' operations. To support one-to-many operations, higher levels of human-autonomy teaming are required, where human operators collaborate with autonomous agents through the use of adaptive Human-Machine Interfaces and Interactions (HMI2). In this paper, the one-to-many concept is applied to a bushfire-fighting scenario. The paper presents the UAV avionics systems design along with the Ground Control Station (GCS) design, which features a number of emerging HMI2 concepts.

Progress in Aerospace Sciences, 2018

Technological advances in avionics systems and components have facilitated the introduction of pr... more Technological advances in avionics systems and components have facilitated the introduction of progressively more integrated and automated Human-Machine Interfaces and Interactions (HMI2) on-board civil and military aircraft. A detailed review of these HMI2 evolutions is presented, addressing both manned aircraft (fixed and rotary wing) and Remotely Piloted Aircraft System (RPAS) specificities for the most fundamental flight tasks: aviate, navigate, communicate and manage. Due to the large variability in mission requirements, greater emphasis is given to safety-critical displays, command and control functions as well as associated technology developments. Additionally, a top-level definition of RPAS mission-essential functionalities is provided, addressing planning and real-time decision support for single and multi-aircraft operations. While current displays are able to integrate and fuse information from several sources to perform a range of different functions, these displays have limited adaptability. Further development to increase HMI2 adaptiveness has significant potential to enhance the human operator’s effectiveness, thereby contributing to safer and more efficient operations. The adaptive HMI2 concepts in the literature contain three common elements. These elements comprise the ability to assess the system and environmental states; the ability to assess the operator states; and the ability to adapt the HMI2 according to the first two elements. While still an emerging area of research, HMI2 adaptation driven by human performance and cognition has the potential to greatly enhance human-machine teaming through varying the system support according to the user’s needs. However, one of the outstanding challenges in the design of such adaptive systems is the development of suitable models and algorithms to describe human performance and cognitive states based on real-time sensor measurements. After reviewing the state-of-research in human performance assessment and adaptation techniques, detailed recommendations are provided to support the integration of such techniques in the HMI2 of future Communications, Navigations, Surveillance (CNS), Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems.

Avionics and Air Traffic Management (ATM) systems are evolving with the introduction of progressi... more Avionics and Air Traffic Management (ATM) systems are evolving with the introduction of progressively higher levels of automation, towards attaining the ambitious operational, technical and safety enhancements required to sustain the present growth of global air traffic. This article presents novel 4-Dimensional Trajectory (4DT) functionalities that are being developed for integration in ATM and avionics systems to support Trajectory Based Operations (TBO). The 4DT planning process, which is the main focus of the article, is supported by a custom multi-objective variant of state-of-the-art optimal control algorithms, incorporating various operational, economic and environmental factors. Capitalizing on the higher theoretical accuracy offered by optimal control algorithms compared to other methods, a key feature of the proposed approach is the introduction of a post-processing stage to ensure that the mathematically optimal trajectories are translated into a set of standardized 4DT descriptors, which can be flown by state-of-the-art automatic flight control systems. Additionally, to support air-ground 4DT intent negotiation and validation in the TBO context, the 4DT post-processing ensures that optimal trajectories are synthetically described by a limited number of parameters, minimizing the bandwidth requirements imposed on airborne data links. Simulation-based verification activities addressing operational efficiency improvements and computational performance in the terminal area ATM context support the viability of the proposed 4DT planning functionality for online tactical TBO.

This paper presents new efficient guidance algorithms allowing Unmanned Aircraft Systems (UAS) to... more This paper presents new efficient guidance algorithms allowing Unmanned Aircraft Systems (UAS) to avoid a variety of Global Navigation Satellite System (GNSS) continuity and integrity performance threats detected by an Aircraft Based Augmentation System (ABAS). In particular, the UAS guidance problem is formulated as an optimal control-based Multi-Objective Trajectory Optimization (MOTO) problem subject to suitable dynamic and geometric constraints. Direct transcription methods of the global orthogonal collocation (pseudospectral) family are exploited for the solution of the MOTO problem, generating optimal trajectories for curved GNSS approaches in real-time. Three degrees-of-freedom aircraft dynamics models and suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data are utilised in the MOTO solution algorithm. The performance of the proposed MOTO algorithm is evaluated in representative simulation case studies adopting the JAVELIN UAS as the reference platform. The paper focusses on descent and initial curved GNSS approach phases in a Terminal Maneuvering Area (TMA) scenario, where multiple manned/unmanned aircraft converge on the same short and curved final GNSS approach leg. The results show that the adoption of MOTO based on pseudospectral methods allows an efficient exploitation of ABAS model-predictive augmentation features in online GNSS guidance tasks, supporting the calculation of suitable arrival trajectories in 7 to 16 s using a normal PC.

Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospa... more Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospace engineering as they combine the complementary advantages of internal combustion and electric propulsion technologies while limiting the environmental emissions. Despite the promising benefits, the insufficient energy densities and specific energies of electrical storage devices are major challenges as they induce severe weight and volume penalties. Significant opportunities are nonetheless emerging thanks to optimised propulsive profiles, energy harvesting techniques and more electric aircraft technologies. To support further research on hybrid electric aircraft, the aim of this study is to develop a HEPS retrofit design methodology for existing Remotely Piloted Aircraft Systems (RPAS). The implemented HEPS models use power state variables, allowing more accurate predictions of energy converter efficiency than with power-based approaches. Data from commercially available products is introduced and a case study is presented assuming a reference RPAS platform and performing parametric studies for traditional, electric and hybrid configurations. Range and endurance performances are investigated in depth and the most significant dependencies on design parameters are analysed. The results suggest that HEPS technology represents a viable trade-off solution in small-to-medium size RPAS, promoting the mitigation of noxious and greenhouse emissions while providing adequate range and endurance performance.

This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors us... more This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for intelligent transport systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncertainty analysis method is presented for ranging error budget prediction in acoustic navigation applications. Considering the design challenges associated with monostatic and multi-static sensor implementations and looking at the performance predictions for different possible configurations, acoustic sensors show clear promises in navigation, proximity sensing, as well as obstacle detection and tracking. The integration of acoustic sensors in multi-sensor navigation systems is also considered towards the end of the paper and a low Size, Weight and Power, and Cost (SWaP-C) sensor integration architecture is presented for possible introduction in air and surface navigation systems.

A unified approach to cooperative and non-cooperative Separation Assurance and Collision Avoidanc... more A unified approach to cooperative and non-cooperative Separation Assurance and Collision Avoidance (SA&CA) is presented addressing the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into all classes of airspace. Additionally, the emerging UAS Traffic Management (UTM) system requirements are captured and addressed in this novel unified framework. In a multiplatform UTM system implementation, the errors in navigation and tracking measurements associated to each manned/unmanned platform in a certain airspace region (as seen by all other platforms in that region), are combined statistically to generate a Position Uncertainty Volume (PUV). Successively, the PUV is inflated by considering the traffic relative dynamics, leading to the generation of avoidance volumes (dynamic geo-fences) at discrete time intervals. Case studies are presented for evaluating the feasibility of the approach in an urban environment. In this approach, real-time and off-line determination of the UAS safe-to-fly envelope is performed based on the installed avionics sensors and on the own/intruder platform dynamics. Additionally, the SA&CA models developed in this approach support an identification of the UAS sensors required to safely operate in specific portions of the host aircraft operational flight envelope. The resulting build-up of SA&CA design and operational requirements allows a detailed definition of the UAS safety case, thereby providing a pathway to certification.

Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospa... more Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospace engineering as they combine the complementary advantages of internal combustion and electric propulsion technologies while limiting the environmental emissions. Despite the promising benefits, the insufficient energy densities and specific energies of electrical storage devices are major challenges as they induce severe weight and volume penalties. Significant opportunities are nonetheless emerging thanks to optimised propulsive profiles, energy harvesting techniques and more electric aircraft technologies. To support further research on hybrid electric aircraft, the aim of this study is to develop a HEPS retrofit design methodology for existing Remotely Piloted Aircraft Systems (RPAS). The implemented HEPS models use power state variables, allowing more accurate predictions of energy converter efficiency than with power-based approaches. Data from commercially available products is introduced and a case study is presented assuming a reference RPAS platform and performing parametric studies for traditional, electric and hybrid configurations. Range and endurance performances are investigated in depth and the most significant dependencies on design parameters are analysed. The results suggest that HEPS technology represents a viable trade-off solution in small-to-medium size RPAS, promoting the mitigation of noxious and greenhouse emissions while providing adequate range and endurance performance.

This paper describes the 4-Dimensional Trajectory (4DT) optimisation algorithm implemented to avo... more This paper describes the 4-Dimensional Trajectory (4DT) optimisation algorithm implemented to avoid a variety of Global Navigation Satellite System (GNSS) signal degradations predicted by an Avionics Based Integrity Augmentation system (ABIA). The paper focusses on descent and initial curved GNSS approach phases in a dense Terminal Manoeuvring Area (TMA) scenario, with multiple aircraft converging on the same short and curved final GNSS approach leg. The reference platform for this study is the Javelin Remotely Piloted Aircraft System (RPAS). The 4DT optimisation algorithm implements three degrees-of-freedom aircraft dynamics models as well as suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data. Direct transcription methods of the global orthogonal (pseudospectral) collocation family are implemented, generating optimal high-integrity trajectories for curved GNSS approaches in real-time. The optimal trajectories calculated by the pseudospectral method are subsequently processed by control input smoothing and manoeuvre identification algorithms to translate the mathematical optimum into a pilot-/autopilot-flyable and concisely described 4DT intent. The characteristics of the proposed 4DT optimisation algorithm are evaluated in representative simulation case studies targeting short and curved GNSS approaches in dense TMA conditions, showing very satisfactory performance.

A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection... more A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection-constraint methods is proposed to solve multi-objective aircraft trajectory optimisation problems formulated as nonlinear optimal control problems. This technique is applicable to a variety of next-generation avionics and Air Traffic Management (ATM) Decision Support Systems (DSS) for strategic and tactical replanning operations. These include the future Flight Management Systems (FMS) and the 4-Dimensional Trajectory (4DT) planning and intent negotiation/validation tools envisaged by SESAR and NextGen for a global implementation. In particular, after describing the implemented PSD method, the adaptive bisection-constraint method is presented to allow an efficient solution of problems in which two or multiple performance indices are to be minimized simultaneously. Initial simulation case studies were performed adopting suitable aircraft dynamics models and addressing a classical vertical trajectory optimisation problem with two objectives simultaneously. Subsequently, a more advanced 4DT simulation case study is presented with a focus on representative ATM optimisation objectives in the Terminal Manoeuvring Area (TMA). The simulation results are analysed in-depth and corroborated by flight performance analysis, supporting the validity of the proposed computational techniques.

In recent years Air Traffic Flow Management (ATFM) has become pertinent even in regions without s... more In recent years Air Traffic Flow Management (ATFM) has become pertinent even in regions without sustained overload conditions caused by dense traffic operations. Increasing traffic volumes in the face of constrained resources has created peak congestion at specific locations and times in many areas of the world. Increased environmental awareness and economic drivers have combined to create a resurgent interest in ATFM as evidenced by a spate of recent ATFM conferences and workshops mediated by official bodies such as ICAO, IATA, CANSO the FAA and Eurocontrol. Significant ATFM acquisitions in the last 5 years include South Africa, Australia and India. Singapore, Thailand and Korea are all expected to procure ATFM systems within a year while China is expected to develop a bespoke system. Asia-Pacific nations are particularly pro-active given the traffic growth projections for the region (by 2050 half of all air traffic will be to, from or within the Asia-Pacific region). National authorities now have access to recently published international standards to guide the development of national and regional operational concepts for ATFM, geared to Communications, Navigation, Surveillance/Air Traffic Management and Avionics (CNS+A) evolutions. This paper critically reviews the field to determine which ATFM research and development efforts hold the best promise for practical technological implementations, offering clear benefits both in terms of enhanced safety and efficiency in times of growing air traffic. An evolutionary approach is adopted starting from an ontology of current ATFM techniques and proceeding to identify the technological and regulatory evolutions required in the future CNS+A context, as the aviation industry moves forward with a clearer understanding of emerging operational needs, the geo-political realities of regional collaboration and the impending needs of global harmonization.

With Unmanned Aircraft System (UAS) being developed and deployed for an increasing number of appl... more With Unmanned Aircraft System (UAS) being developed and deployed for an increasing number of applications, it is essential to meet demanding separation assurance and navigation performance requirements, especially considering the current evolutions of the UAS Traffic Management (UTM) research framework. However, in dense urban environments characterized by tall buildings and complex man-made structures, Global Navigation Satellite System (GNSS) is prone to data degradations or complete loss of signal due to multipath effects, interference or antenna obscuration. Furthermore, there is always a risk of jamming and spoofing of GNSS signals, with low cost civilian GNSS receivers being more vulnerable to a spoof attack. Therefore, a number of Signals of Opportunity (SoOP) techniques are being explored to improve the navigation performance when UAS are employed in urban canyons. Electromagnetic signals found in urban environments including analogue/digital radio, analogue/digital television, Wi-Fi, Global System for Mobile Communications (GSM) and Code Division Multiple Access (CDMA) based signals are considered to model the system performance parameters. Implementation methods for exploiting SoOP such as Angle of Arrival (AOA), Time of Arrival (TOA), Received Signal Strength (RSS) and Time Difference of Arrival (TDOA) are introduced and compared. Integration of SoOP techniques in novel low-cost Navigation and Guidance Systems (NGS) is also investigated. As SoOP are not natively intended to be used for navigation purposes, no single source of SoOP for navigation can work in all environments and hence a SoOP source has to be selected based on specific requirements in the considered urban environment. Constraints of power and weight on the Unmanned Aerial Vehicle (UAV) besides hardware and software costs are also factors that are considered when selecting appropriate SoOP signal sources. Therefore, there is a clear opportunity for considerable savings in both infrastructure and energy costs by providing a low-cost and low-volume integrated NGS solution for trusted autonomous aerial operations.

Journal of Air Transport Management, 2021

Multi-airport systems are growing in number and size globally, despite being afflicted by known i... more Multi-airport systems are growing in number and size globally, despite being afflicted by known inefficiencies due to the interferences between the flows of neighbouring airports. A macroscopic empirical approach is proposed in this paper to estimate the capacity penalties and demonstrated by a numerical case study for Beijing, which is projected to become one of the busiest metroplexes in Asia. The Pareto envelopes of the theoretical and observed peak hour capacities are statistically analysed to quantify the penalties in a comparable metroplex and are subsequently modulated by a sigmoid correlation function. The analysis predicts the practical capacity of Daxing, the penalty incurred by the pre-existing Capital airport and by the total multi-airport system. Various findings are drawn and discussed, highlighting the needs for further research.

Computers, 2021

With increasingly higher levels of automation in aerospace decision support systems, it is impera... more With increasingly higher levels of automation in aerospace decision support systems, it is imperative that the human operator maintains the required level of situational awareness in different operational conditions and a central role in the decision-making process. While current aerospace systems and interfaces are limited in their adaptability, a Cognitive Human Machine System (CHMS) aims to perform dynamic, real-time system adaptation by estimating the cognitive states of the human operator. Nevertheless, to reliably drive system adaptation of current and emerging aerospace systems, there is a need to accurately and repeatably estimate cognitive states, particularly for Mental Workload (MWL), in real-time. As part of this study, two sessions were performed during a Multi Attribute Task Battery (MATB) scenario, including a session for offline calibration and validation and a session for online validation of eleven multimodal inference models of MWL. The multimodal inference model implemented included an Adaptive Neuro Fuzzy Inference System (ANFIS), which was used in different configurations to fuse data from an Electroencephalogram (EEG) model’s output, four eye activity features and a control input feature. The online validation of the ANFIS models produced good results, while the best performing model (containing all four eye activity features and the control input feature) showed an average Mean Absolute Error (MAE) = 0.67 ± 0.18 and Correlation Coefficient (CC) = 0.71 ± 0.15. The remaining six ANFIS models included data from the EEG model’s output, which had an offset discrepancy. This resulted in an equivalent offset for the online multimodal fusion. Nonetheless, the efficacy of these ANFIS models could be confirmed by the pairwise correlation with the task level, where one model demonstrated a CC = 0.77 ± 0.06, which was the highest among all of the ANFIS models tested. Hence, this study demonstrates the suitability for online multimodal fusion of features extracted from EEG signals, eye activity and control inputs to produce an accurate and repeatable inference of MWL.

Atmosphere, 2021

Atmospheric effects have a significant impact on the performance of airborne and space laser syst... more Atmospheric effects have a significant impact on the performance of airborne and space laser systems. Traditional models used to predict propagation effects rely heavily on simplified assumptions of the atmospheric properties and their interactions with laser systems. In the engineering domain, these models need to be continually improved in order to develop tools that can predict laser beam propagation with high accuracy and for a wide range of practical applications such as LIDAR (light detection and ranging), free-space optical communications, remote sensing, etc. The underlying causes of laser beam attenuation in the atmosphere are examined in this paper, with a focus on the dominant linear effects: absorption, scattering, turbulence, and non-linear thermal effects such as blooming, kinetic cooling, and bleaching. These phenomena are quantitatively analyzed, highlighting the implications of the various assumptions made in current modeling approaches. Absorption and scattering, as the dominant causes of attenuation, are generally well captured in existing models and tools, but the impacts of non-linear phenomena are typically not well described as they tend to be application specific. Atmospheric radiative transfer codes, such as MODTRAN, ARTS, etc., and the associated spectral databases, such as HITRAN, are the existing tools that implement state-of-the-art models to quantify the total propagative effects on laser systems. These tools are widely used to analyze system performance, both for design and test/evaluation purposes. However, present day atmospheric radiative transfer codes make several assumptions that reduce accuracy in favor of faster processing. In this paper, the atmospheric radiative transfer models are reviewed highlighting the associated methodologies, assumptions, and limitations. Empirical models are found to offer a robust analysis of atmospheric propagation, which is particularly well-suited for design, development, test and evaluation (DDT&E) purposes. As such, empirical, semi-empirical, and ensemble methodologies are recommended to complement and augment the existing atmospheric radiative transfer codes. There is scope to evolve the numerical codes and empirical approaches to better suit aerospace applications, where fast analysis is required over a range of slant paths, incidence angles, altitudes, and atmospheric conditions, which are not exhaustively captured in current performance assessment methods.

Progress in Aerospace Sciences, 2019

Progress in spaceflight research has led to the introduction of various manned and unmanned reusa... more Progress in spaceflight research has led to the introduction of various manned and unmanned reusable space vehicle concepts, opening up uncharted opportunities for the newborn space transport industry. For future space transport operations to be technically and commercially viable, it is critical that an acceptable level of safety is provided, requiring the development of novel mission planning and decision support tools that utilize advanced Communication, Navigation and Surveillance (CNS) technologies, and allowing a seamless integration of space operations in the current Air Traffic Management (ATM) network. A review of emerging platform operational concepts is conducted, highlighting both the challenges and the opportunities brought in by the integration with conventional atmospheric air transport. Common launch and re-entry planning methodologies are then discussed, where the physical and computational limitations of these approaches are identified and applicability to future commercial space transport operations is assessed. Attention is then turned to the on-orbit phase, where the unique hazards of the space environment are examined, followed by an overview to the necessary elements required for space object de-confliction and collision avoidance modelling. The regulatory framework evolutions required for spacecraft operations are then discussed, with a focus on space debris mitigation strategies and operational risk assessment. Within the atmospheric domain, possible extensions and alternatives to the conventional airspace segregation approaches are identified including promising Air Traffic Flow Management (ATFM) techniques to facilitate the integration of new-entrant platforms. Lastly, recent modelling approaches to meet on-orbit risk criteria are discussed and evolutionary requirements to improve current operational procedures are identified. These insights will inform future research on CNS/ATM and Avionics (CNS + A) systems and associated cyber-physical architectures for Space Traffic Management (STM).

AIAA Guidance, Navigation and Control Conference (Scitech 2019), 2019

This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on ... more This paper presents a novel indoor navigation technique using acoustic sensors, with emphasis on performance modeling and the system layout. Acoustic transmitters are arranged at known fixed locations and broadcast their respective signals following a Time Division Multiple Access (TDMA) scheme. The receiver position is calculated based on Time of Arrival (TOA) based ranging measurements from a minimum of four transmitters. The transmitters are arranged optimally to minimize Position Dilution of Precision (PDOP) as well as maximizing sensor availability. The proposed technique can provide accurate navigation observables in indoor environments, where conventional satellite-based navigation systems cannot deliver the required Position, Velocity, and Time (PVT) data. Additionally, being based on acoustic signals, it is immune to signal-in-space electromagnetic interferences. The TDMA based acoustic navigation system is described, with potential errors in ranging due to Doppler effect, multipath, atmospheric propagation, and signal delays. The error in positioning due to platform dynamics is also discussed. This analysis will lead to an optimized arrangement of transmitters supporting the future ground and flight experimental activities.

Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil, 2018

Unmanned Aircraft Systems (UAS), also known as drones, are capable of autonomously carrying out a... more Unmanned Aircraft Systems (UAS), also known as drones, are capable of autonomously carrying out an increasing number of duties with substantially greater efficiency compared to human intervention. UAS researchers aim to enhance the levels of safety, mission effectiveness and autonomy, as well as explore additional capabilities. Crop health monitoring is a very promising application of UAS as the early detection of plant diseases can supplement traditional crop monitoring techniques (such as visual observation) to support timely mitigation, thereby offering substantial benefits to crop yield and quality. This paper presents new UAS-borne Electro-Optics/Infrared (EO/IR) systems based on bistatic Light Detection and Ranging (LIDAR) for early detection of crop diseases. The proposed bistatic LIDAR system measures over extended observation periods above the crop canopy anomalies in carbon dioxide (CO 2) concentration potentially associated with disruptions in the plant photosynthesis. In particular, this paper discusses the application of the bistatic LIDAR to the early detection of powdery mildew in strawberry crops and presents the initial modelling and simulation activities performed to predict the sensor performance. Based on the results of this analysis, a plan for future experimental activities is also developed.

Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil, 2018

The steadily increasing air traffic demand has highlighted a need to evolve existing Air Traffic ... more The steadily increasing air traffic demand has highlighted a need to evolve existing Air Traffic Flow Management (ATFM) methodologies by increasing automation support in airborne and ground-based systems and more flexible modulation of air traffic controller workload. Dynamic Airspace Management (DAM) aims at optimising the demand-capacity balance in all airspace regions at all times with a particular focus on capacity modulation measures. In this paper, we propose a novel DAM approach supporting the dynamic morphing of airspace sector boundaries based on an optimal-control formulation. The Eulerian continuity principle is used to model the air traffic flow at a macroscopic scale and workload-based capacity constraints are considered to determine the optimal variations in sector volumes. The demand levels are determined and the traffic flow theory based on the principle of continuity is used to propagate the demand across airspace sectors, approximated as 2D polygons. The newly developed sector morphing framework will be integrated into next-generation ATFM decision support systems to drive adaptive human-machine interfaces and interactions supporting more efficient exploitation of airspace resources.

Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil, 2018

Unmanned Aircraft Systems (UAS) offer many opportunities in a wide range of industries to support... more Unmanned Aircraft Systems (UAS) offer many opportunities in a wide range of industries to support remote sensing and surveillance. While platform autonomy and intelligence have seen large advances in recent decades, a key challenge is the operation of multiple Unmanned Aerial Vehicles (UAV) by a single operator in 'one-to-many' operations. To support one-to-many operations, higher levels of human-autonomy teaming are required, where human operators collaborate with autonomous agents through the use of adaptive Human-Machine Interfaces and Interactions (HMI2). In this paper, the one-to-many concept is applied to a bushfire-fighting scenario. The paper presents the UAV avionics systems design along with the Ground Control Station (GCS) design, which features a number of emerging HMI2 concepts.

Progress in Aerospace Sciences, 2018

Technological advances in avionics systems and components have facilitated the introduction of pr... more Technological advances in avionics systems and components have facilitated the introduction of progressively more integrated and automated Human-Machine Interfaces and Interactions (HMI2) on-board civil and military aircraft. A detailed review of these HMI2 evolutions is presented, addressing both manned aircraft (fixed and rotary wing) and Remotely Piloted Aircraft System (RPAS) specificities for the most fundamental flight tasks: aviate, navigate, communicate and manage. Due to the large variability in mission requirements, greater emphasis is given to safety-critical displays, command and control functions as well as associated technology developments. Additionally, a top-level definition of RPAS mission-essential functionalities is provided, addressing planning and real-time decision support for single and multi-aircraft operations. While current displays are able to integrate and fuse information from several sources to perform a range of different functions, these displays have limited adaptability. Further development to increase HMI2 adaptiveness has significant potential to enhance the human operator’s effectiveness, thereby contributing to safer and more efficient operations. The adaptive HMI2 concepts in the literature contain three common elements. These elements comprise the ability to assess the system and environmental states; the ability to assess the operator states; and the ability to adapt the HMI2 according to the first two elements. While still an emerging area of research, HMI2 adaptation driven by human performance and cognition has the potential to greatly enhance human-machine teaming through varying the system support according to the user’s needs. However, one of the outstanding challenges in the design of such adaptive systems is the development of suitable models and algorithms to describe human performance and cognitive states based on real-time sensor measurements. After reviewing the state-of-research in human performance assessment and adaptation techniques, detailed recommendations are provided to support the integration of such techniques in the HMI2 of future Communications, Navigations, Surveillance (CNS), Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems.

Avionics and Air Traffic Management (ATM) systems are evolving with the introduction of progressi... more Avionics and Air Traffic Management (ATM) systems are evolving with the introduction of progressively higher levels of automation, towards attaining the ambitious operational, technical and safety enhancements required to sustain the present growth of global air traffic. This article presents novel 4-Dimensional Trajectory (4DT) functionalities that are being developed for integration in ATM and avionics systems to support Trajectory Based Operations (TBO). The 4DT planning process, which is the main focus of the article, is supported by a custom multi-objective variant of state-of-the-art optimal control algorithms, incorporating various operational, economic and environmental factors. Capitalizing on the higher theoretical accuracy offered by optimal control algorithms compared to other methods, a key feature of the proposed approach is the introduction of a post-processing stage to ensure that the mathematically optimal trajectories are translated into a set of standardized 4DT descriptors, which can be flown by state-of-the-art automatic flight control systems. Additionally, to support air-ground 4DT intent negotiation and validation in the TBO context, the 4DT post-processing ensures that optimal trajectories are synthetically described by a limited number of parameters, minimizing the bandwidth requirements imposed on airborne data links. Simulation-based verification activities addressing operational efficiency improvements and computational performance in the terminal area ATM context support the viability of the proposed 4DT planning functionality for online tactical TBO.

This paper presents new efficient guidance algorithms allowing Unmanned Aircraft Systems (UAS) to... more This paper presents new efficient guidance algorithms allowing Unmanned Aircraft Systems (UAS) to avoid a variety of Global Navigation Satellite System (GNSS) continuity and integrity performance threats detected by an Aircraft Based Augmentation System (ABAS). In particular, the UAS guidance problem is formulated as an optimal control-based Multi-Objective Trajectory Optimization (MOTO) problem subject to suitable dynamic and geometric constraints. Direct transcription methods of the global orthogonal collocation (pseudospectral) family are exploited for the solution of the MOTO problem, generating optimal trajectories for curved GNSS approaches in real-time. Three degrees-of-freedom aircraft dynamics models and suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data are utilised in the MOTO solution algorithm. The performance of the proposed MOTO algorithm is evaluated in representative simulation case studies adopting the JAVELIN UAS as the reference platform. The paper focusses on descent and initial curved GNSS approach phases in a Terminal Maneuvering Area (TMA) scenario, where multiple manned/unmanned aircraft converge on the same short and curved final GNSS approach leg. The results show that the adoption of MOTO based on pseudospectral methods allows an efficient exploitation of ABAS model-predictive augmentation features in online GNSS guidance tasks, supporting the calculation of suitable arrival trajectories in 7 to 16 s using a normal PC.

Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospa... more Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospace engineering as they combine the complementary advantages of internal combustion and electric propulsion technologies while limiting the environmental emissions. Despite the promising benefits, the insufficient energy densities and specific energies of electrical storage devices are major challenges as they induce severe weight and volume penalties. Significant opportunities are nonetheless emerging thanks to optimised propulsive profiles, energy harvesting techniques and more electric aircraft technologies. To support further research on hybrid electric aircraft, the aim of this study is to develop a HEPS retrofit design methodology for existing Remotely Piloted Aircraft Systems (RPAS). The implemented HEPS models use power state variables, allowing more accurate predictions of energy converter efficiency than with power-based approaches. Data from commercially available products is introduced and a case study is presented assuming a reference RPAS platform and performing parametric studies for traditional, electric and hybrid configurations. Range and endurance performances are investigated in depth and the most significant dependencies on design parameters are analysed. The results suggest that HEPS technology represents a viable trade-off solution in small-to-medium size RPAS, promoting the mitigation of noxious and greenhouse emissions while providing adequate range and endurance performance.

This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors us... more This paper presents the state-of-the-art and reviews the state-of-research of acoustic sensors used for a variety of navigation and guidance applications on air and surface vehicles. In particular, this paper focuses on echolocation, which is widely utilized in nature by certain mammals (e.g., cetaceans and bats). Although acoustic sensors have been extensively adopted in various engineering applications, their use in navigation and guidance systems is yet to be fully exploited. This technology has clear potential for applications in air and surface navigation/guidance for intelligent transport systems (ITS), especially considering air and surface operations indoors and in other environments where satellite positioning is not available. Propagation of sound in the atmosphere is discussed in detail, with all potential attenuation sources taken into account. The errors introduced in echolocation measurements due to Doppler, multipath and atmospheric effects are discussed, and an uncertainty analysis method is presented for ranging error budget prediction in acoustic navigation applications. Considering the design challenges associated with monostatic and multi-static sensor implementations and looking at the performance predictions for different possible configurations, acoustic sensors show clear promises in navigation, proximity sensing, as well as obstacle detection and tracking. The integration of acoustic sensors in multi-sensor navigation systems is also considered towards the end of the paper and a low Size, Weight and Power, and Cost (SWaP-C) sensor integration architecture is presented for possible introduction in air and surface navigation systems.

A unified approach to cooperative and non-cooperative Separation Assurance and Collision Avoidanc... more A unified approach to cooperative and non-cooperative Separation Assurance and Collision Avoidance (SA&CA) is presented addressing the technical and regulatory challenges of Unmanned Aircraft Systems (UAS) integration into all classes of airspace. Additionally, the emerging UAS Traffic Management (UTM) system requirements are captured and addressed in this novel unified framework. In a multiplatform UTM system implementation, the errors in navigation and tracking measurements associated to each manned/unmanned platform in a certain airspace region (as seen by all other platforms in that region), are combined statistically to generate a Position Uncertainty Volume (PUV). Successively, the PUV is inflated by considering the traffic relative dynamics, leading to the generation of avoidance volumes (dynamic geo-fences) at discrete time intervals. Case studies are presented for evaluating the feasibility of the approach in an urban environment. In this approach, real-time and off-line determination of the UAS safe-to-fly envelope is performed based on the installed avionics sensors and on the own/intruder platform dynamics. Additionally, the SA&CA models developed in this approach support an identification of the UAS sensors required to safely operate in specific portions of the host aircraft operational flight envelope. The resulting build-up of SA&CA design and operational requirements allows a detailed definition of the UAS safety case, thereby providing a pathway to certification.

Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospa... more Hybrid-Electric Propulsion Systems (HEPS) have emerged as a promising area of research in aerospace engineering as they combine the complementary advantages of internal combustion and electric propulsion technologies while limiting the environmental emissions. Despite the promising benefits, the insufficient energy densities and specific energies of electrical storage devices are major challenges as they induce severe weight and volume penalties. Significant opportunities are nonetheless emerging thanks to optimised propulsive profiles, energy harvesting techniques and more electric aircraft technologies. To support further research on hybrid electric aircraft, the aim of this study is to develop a HEPS retrofit design methodology for existing Remotely Piloted Aircraft Systems (RPAS). The implemented HEPS models use power state variables, allowing more accurate predictions of energy converter efficiency than with power-based approaches. Data from commercially available products is introduced and a case study is presented assuming a reference RPAS platform and performing parametric studies for traditional, electric and hybrid configurations. Range and endurance performances are investigated in depth and the most significant dependencies on design parameters are analysed. The results suggest that HEPS technology represents a viable trade-off solution in small-to-medium size RPAS, promoting the mitigation of noxious and greenhouse emissions while providing adequate range and endurance performance.

This paper describes the 4-Dimensional Trajectory (4DT) optimisation algorithm implemented to avo... more This paper describes the 4-Dimensional Trajectory (4DT) optimisation algorithm implemented to avoid a variety of Global Navigation Satellite System (GNSS) signal degradations predicted by an Avionics Based Integrity Augmentation system (ABIA). The paper focusses on descent and initial curved GNSS approach phases in a dense Terminal Manoeuvring Area (TMA) scenario, with multiple aircraft converging on the same short and curved final GNSS approach leg. The reference platform for this study is the Javelin Remotely Piloted Aircraft System (RPAS). The 4DT optimisation algorithm implements three degrees-of-freedom aircraft dynamics models as well as suitable GNSS satellite visibility models based on Global Positioning System (GPS) constellation ephemeris data. Direct transcription methods of the global orthogonal (pseudospectral) collocation family are implemented, generating optimal high-integrity trajectories for curved GNSS approaches in real-time. The optimal trajectories calculated by the pseudospectral method are subsequently processed by control input smoothing and manoeuvre identification algorithms to translate the mathematical optimum into a pilot-/autopilot-flyable and concisely described 4DT intent. The characteristics of the proposed 4DT optimisation algorithm are evaluated in representative simulation case studies targeting short and curved GNSS approaches in dense TMA conditions, showing very satisfactory performance.

A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection... more A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection-constraint methods is proposed to solve multi-objective aircraft trajectory optimisation problems formulated as nonlinear optimal control problems. This technique is applicable to a variety of next-generation avionics and Air Traffic Management (ATM) Decision Support Systems (DSS) for strategic and tactical replanning operations. These include the future Flight Management Systems (FMS) and the 4-Dimensional Trajectory (4DT) planning and intent negotiation/validation tools envisaged by SESAR and NextGen for a global implementation. In particular, after describing the implemented PSD method, the adaptive bisection-constraint method is presented to allow an efficient solution of problems in which two or multiple performance indices are to be minimized simultaneously. Initial simulation case studies were performed adopting suitable aircraft dynamics models and addressing a classical vertical trajectory optimisation problem with two objectives simultaneously. Subsequently, a more advanced 4DT simulation case study is presented with a focus on representative ATM optimisation objectives in the Terminal Manoeuvring Area (TMA). The simulation results are analysed in-depth and corroborated by flight performance analysis, supporting the validity of the proposed computational techniques.

In recent years Air Traffic Flow Management (ATFM) has become pertinent even in regions without s... more In recent years Air Traffic Flow Management (ATFM) has become pertinent even in regions without sustained overload conditions caused by dense traffic operations. Increasing traffic volumes in the face of constrained resources has created peak congestion at specific locations and times in many areas of the world. Increased environmental awareness and economic drivers have combined to create a resurgent interest in ATFM as evidenced by a spate of recent ATFM conferences and workshops mediated by official bodies such as ICAO, IATA, CANSO the FAA and Eurocontrol. Significant ATFM acquisitions in the last 5 years include South Africa, Australia and India. Singapore, Thailand and Korea are all expected to procure ATFM systems within a year while China is expected to develop a bespoke system. Asia-Pacific nations are particularly pro-active given the traffic growth projections for the region (by 2050 half of all air traffic will be to, from or within the Asia-Pacific region). National authorities now have access to recently published international standards to guide the development of national and regional operational concepts for ATFM, geared to Communications, Navigation, Surveillance/Air Traffic Management and Avionics (CNS+A) evolutions. This paper critically reviews the field to determine which ATFM research and development efforts hold the best promise for practical technological implementations, offering clear benefits both in terms of enhanced safety and efficiency in times of growing air traffic. An evolutionary approach is adopted starting from an ontology of current ATFM techniques and proceeding to identify the technological and regulatory evolutions required in the future CNS+A context, as the aviation industry moves forward with a clearer understanding of emerging operational needs, the geo-political realities of regional collaboration and the impending needs of global harmonization.

With Unmanned Aircraft System (UAS) being developed and deployed for an increasing number of appl... more With Unmanned Aircraft System (UAS) being developed and deployed for an increasing number of applications, it is essential to meet demanding separation assurance and navigation performance requirements, especially considering the current evolutions of the UAS Traffic Management (UTM) research framework. However, in dense urban environments characterized by tall buildings and complex man-made structures, Global Navigation Satellite System (GNSS) is prone to data degradations or complete loss of signal due to multipath effects, interference or antenna obscuration. Furthermore, there is always a risk of jamming and spoofing of GNSS signals, with low cost civilian GNSS receivers being more vulnerable to a spoof attack. Therefore, a number of Signals of Opportunity (SoOP) techniques are being explored to improve the navigation performance when UAS are employed in urban canyons. Electromagnetic signals found in urban environments including analogue/digital radio, analogue/digital television, Wi-Fi, Global System for Mobile Communications (GSM) and Code Division Multiple Access (CDMA) based signals are considered to model the system performance parameters. Implementation methods for exploiting SoOP such as Angle of Arrival (AOA), Time of Arrival (TOA), Received Signal Strength (RSS) and Time Difference of Arrival (TDOA) are introduced and compared. Integration of SoOP techniques in novel low-cost Navigation and Guidance Systems (NGS) is also investigated. As SoOP are not natively intended to be used for navigation purposes, no single source of SoOP for navigation can work in all environments and hence a SoOP source has to be selected based on specific requirements in the considered urban environment. Constraints of power and weight on the Unmanned Aerial Vehicle (UAV) besides hardware and software costs are also factors that are considered when selecting appropriate SoOP signal sources. Therefore, there is a clear opportunity for considerable savings in both infrastructure and energy costs by providing a low-cost and low-volume integrated NGS solution for trusted autonomous aerial operations.