Roberto Sabatini - Profile on Academia.edu (original) (raw)

Papers by Roberto Sabatini

Applied Mechanics and Materials, 2014

This paper presents the concept of operations, architecture and trajectory optimisation algorithm... more This paper presents the concept of operations, architecture and trajectory optimisation algorithms of a Next Generation Flight Management System (NG-FMS). The NG-FMS is developed for Four Dimensional (4D) Intent Based Operations (IBO) in the next generation Communications, Navigation, Surveillance and Air Traffic Management system (CNS+A) context. The NG-FMS, primarily responsible for the aircraft navigation and guidance task, acts as a key enabler for achieving higher level of operational efficiency and mitigating environmental impacts both in manned and unmanned aircraft applications. The NG-FMS is interoperable with the future ground based 4DT Planning, Negotiation and Validation (4-PNV) systems, enabling automated Trajectory/Intent Based Operations (TBO/IBO). After the NG-FMS architecture is presented, the key mathematical models describing the trajectory generation and optimisation modes are introduced. A detailed error analysis is performed and the uncertainties affecting the nominal trajectories are studied to obtain the total NG-FMS error budgets. These are compared with the Required Navigation Performance (RNP) values for the various operational flight tasks considered.

AIAA/IEEE 42st Digital Avionics Systems Conference (DASC 2023) - AESS Public Tutorial, 2023

A surging interest in space launch operations and in Advanced Air Mobility (AAM) concepts is exac... more A surging interest in space launch operations and in Advanced Air Mobility (AAM) concepts is exacerbating the limitations of current practices, still heavily reliant on airspace segregation and not supporting the multimodal/intermodal evolution of air and space transport. For a successful integration of these new transport modes, it is critical that an acceptable level of safety is provided, requiring the development of novel digital tools (e.g., mission planning and decision support systems) that utilize advanced Cyber-Physical Systems (CPS) and Artificial Intelligence (AI) technologies to allow a seamless integration of space operations in the current ATM network. This tutorial addresses the role of Aerospace CPS (ACPS) and AI research to enable the safe, efficient and sustainable development of the air and space transport sector in the next decade. While the technical maturity of propulsive and vehicle technologies is relatively high, there are several opportunities and challenges associated with the adoption of CPS and AI to enable the integration of point-to-point suborbital spaceflight with conventional atmospheric air transport. Current research aims at developing robust and fault-tolerant CPS architectures that ensure trusted autonomous air/space transport operations with the given hardware constraints, despite the uncertainties in physical processes, the limited predictability of environmental conditions, the variability of mission requirements, and the possibility of both cyber and human errors. A key point in these advanced CPS is the control of physical processes from the monitoring of variables and the use of computational intelligence to obtain a deep knowledge of the monitored environment, thus providing timely and more accurate decisions and actions. The growing interconnection of physical and digital elements, and the introduction of highly sophisticated and efficient AI techniques, has led to a new generation of CPS, that is referred to as intelligent (or smart) CPS (iCPS). By equipping physical objects with interfaces to the virtual world, and incorporating intelligent mechanisms to leverage collaboration between these objects, the boundaries between the physical and virtual worlds become blurred. Interactions occurring in the physical world are capable of changing the processing behavior in the virtual world, in a causal relationship that can be exploited for the constant improvement of processes. Exploiting iCPS, intelligent, self-aware, self-managing and self-configuring systems can be built to improve the efficiency of air and space transport, and to build trusted autonomy. However, aviation safety certification is established upon verifying that all possible safety-critical conditions have been identified and verified. Whereas, in the case of AI real-time software evolution cannot be perfectly predicted and verified in advance, this is the real challenge to certification. One solution is to specify AI functional boundaries in correlation with real-time monitoring and validation of AI solution. Implementation can be sequential with practical ground-based AI for scheduling and routing being the starting point. Next in line will be simpler, non-flight critical functions and finally moving on to flight or safety critical systems. Building a certification case requires that the final product operates in all modes and performs consistently and successfully under all actual operational and environmental conditions founded on conformance to the applicable specifications. This is one of the greatest challenges currently faced by the avionics and Air Traffic Management (ATM) industry, which is clearly amplified in the context of future commercial space transport operations. Much attention is currently being devoted to the on-orbit phase, where the unique hazards of the space environment are being examined and the required iCPS evolutions for Resident Space Objects (RSO) de-confliction and collision avoidance are being addressed, including the synergies between existing ground-based tracking systems and rapidly evolving Space-Based Space Surveillance (SBSS) solutions. The advancement of regulatory frameworks supporting spacecraft operations is a conspicuous factor, which requires a holistic approach and extensive government support for the successful development and establishment of sustainable business models, including space debris mitigation strategies, operational risk assessment and liability issues. Within the atmospheric domain, extensions and alternatives to the conventional airspace segregation approaches must be identified including ATM and Air Traffic Flow Management (ATFM) techniques to facilitate the integration of new-entrant platforms. Lastly, adequate modelling approaches to meet on-orbit risk criteria must be developed and evolutionary requirements to improve current operational procedures (and associated regulatory frameworks) must be addressed in order to establish a fully-integrated Multi-Domain Traffic Management (MDTM) framework, including AI-driven situation awareness and decision support mechanisms for air and space traffic management.

AIAA/IEEE 42nd Digital Avionics Systems Conference (DASC 2023), 2023

Thanks to their rapid uptake in various industries, an increasing number of Uninhabited Aircraft ... more Thanks to their rapid uptake in various industries, an increasing number of Uninhabited Aircraft Systems (UAS) and other emerging aerospace platforms is expected to operate in the shared airspace. Viable conflict detection and resolution as well as demand-capacity balancing (DCB) services will be required to ensure the desired level of safety, particularly with the proliferation of Beyond Line-of-Sight (BLOS) operations. This paper proposes a novel UAS Traffic Management (UTM) system DCB functionality adopting multiple Artificial Intelligence (AI) algorithms to manage both regular and emergency situations. The system is based on a fourdimensional trajectory (4DT) planning algorithm with a flexible DCB process and solution framework. The method is not limited to fixed routing, but can also adjust dynamically to evolving conditions. The selected AI techniques are based on the most suitable machine learning and metaheuristic algorithms. Simulation case studies demonstrate that the proposed method allows to achieve a safe and efficient management of dense traffic in low-altitude airspace around cities and suburbs.

IEEE Aerospace and Electronic Systems Magazine, 2023

The integration of unmanned aircraft systems (UAS) in all classes of airspace represents, at the ... more The integration of unmanned aircraft systems (UAS) in all classes of airspace represents, at the same time, an evolutionary and a revolutionary step in air transport operations. As a result, new concepts have emerged for UAS traffic management to support the anticipated traffic density growth and the need for safe beyond visual line-of-sight operations. Closely linked with these developments, urban/advanced air mobility (UAM/AAM) has appeared as a new and disruptive dimension for aviation, potentially enabling mobility of goods and people at a different scale compared with current operations, while also emphasizing the need of seamless integration with the existing air traffic management (ATM) framework. These UAS capabilities are reshaping the future of aviation, but also challenge traditional paradigms, requiring significant advances both in technologies and regulations, while keeping strong links with public communities and the perception of societal benefits. As an example, a key role is played by the progress of communications, navigation and surveillance technologies, such as sense-and-avoid and global navigation satellite systems-resilient, alternate position, navigation, and timing systems, and by the seamless integration of airborne and ground infrastructure within a cyber-aware context. Similarly, significant restructuring of the existing regulatory framework is needed to ensure that the integrity and safety of the AAM/ATM integrated airspace is maintained while enabling autonomous operations with higher technological flexibility and refresh rates. In view of these challenges, the AESS Avionics Systems Panel has compiled a special issue of the AESS Magazine whose focus is set on the most recent research and innovation developments in the field of UAM/AAM and UAS airspace integration. This special issue has been kept broad in scope with the aim of providing a wide overview of the state-of-the-art and development trends in the field, while also addressing the main research gaps that are currently being tackled actively by industry, government and academia.

Sensors, 2023

Recent developments in Distributed Satellite Systems (DSS) have undoubtedly increased mission val... more Recent developments in Distributed Satellite Systems (DSS) have undoubtedly increased mission value due to the ability to reconfigure the spacecraft cluster/formation and incrementally add new or update older satellites in the formation. These features provide inherent benefits, such as increased mission effectiveness, multi-mission capabilities, design flexibility, and so on. Trusted Autonomous Satellite Operation (TASO) are possible owing to the predictive and reactive integrity features offered by Artificial Intelligence (AI), including both on-board satellites and in the ground control segments. To effectively monitor and manage time-critical events such as disaster relief missions, the DSS must be able to reconfigure autonomously. To achieve TASO, the DSS should have reconfiguration capability within the architecture and spacecraft should communicate with each other through an Inter-Satellite Link (ISL). Recent advances in AI, sensing, and computing technologies have resulted in the development of new promising concepts for the safe and efficient operation of the DSS. The combination of these technologies enables trusted autonomy in intelligent DSS (iDSS) operations, allowing for a more responsive and resilient approach to Space Mission Management (SMM) in terms of data collection and processing, especially when using state-of-the-art optical sensors. This research looks into the potential applications of iDSS by proposing a constellation of satellites in Low Earth Orbit (LEO) for near-real-time wildfire management. For spacecraft to continuously monitor Areas of Interest (AOI) in a dynamically changing environment, satellite missions must have extensive coverage, revisit intervals, and reconfiguration capability that iDSS can offer. Our recent work demonstrated the feasibility of AI-based data processing using state-of-the-art on-board astrionics hardware accelerators. Based on these initial results, AI-based software has been successively developed for wildfire detection on-board iDSS satellites. To demonstrate the applicability of the proposed iDSS architecture, simulation case studies are performed considering different geographic locations.

Aerospace, 2023

Space-based Earth Observation (EO) systems have undergone a continuous evolution in the twenty-fi... more Space-based Earth Observation (EO) systems have undergone a continuous evolution in the twenty-first century. With the help of space-based Maritime Domain Awareness (MDA), specially Automatic Identification Systems (AIS), their applicability across the world's waterways, among others, has grown substantially. This research work explores the potential applicability of Synthetic Aperture Radar (SAR) and Distributed Satellite System (DSS) for the MDA operation. A robust multi-baseline Along-Track Interferometric Synthetic Aperture Radar (AT-InSAR) formation flying concept is proposed to combine several along-track baseline observations effectively for single-pass interferometry. Simulation results are presented to support the feasibility of implementing this acquisition mode with autonomous orbit control, using low-thrust actuation suitable for electric propulsion. To improve repeatability, a constellation of this formation concept is also proposed to combine the benefits of the DSS. An MDA application is considered as a hypothetical mission to be solved by this combined approach.

Remote Sensing, 2023

One of the United Nations (UN) Sustainable Development Goals is climate action (SDG-13), and wild... more One of the United Nations (UN) Sustainable Development Goals is climate action (SDG-13), and wildfire is among the catastrophic events that both impact climate change and are aggravated by it. In Australia and other countries, large-scale wildfires have dramatically grown in frequency and size in recent years. These fires threaten the world’s forests and urban woods, cause enormous environmental and property damage, and quite often result in fatalities. As a result of their increasing frequency, there is an ongoing debate over how to handle catastrophic wildfires and mitigate their social, economic, and environmental repercussions. Effective prevention, early warning, and response strategies must be well-planned and carefully coordinated to minimise harmful consequences to people and the environment. Rapid advancements in remote sensing technologies such as ground-based, aerial surveillance vehicle-based, and satellite-based systems have been used for efficient wildfire surveillance. This study focuses on the application of space-borne technology for very accurate fire detection under challenging conditions. Due to the significant advances in artificial intelligence (AI) techniques in recent years, numerous studies have previously been conducted to examine how AI might be applied in various situations. As a result of its special physical and operational requirements, spaceflight has emerged as one of the most challenging application fields. This work contains a feasibility study as well as a model and scenario prototype for a satellite AI system. With the intention of swiftly generating alerts and enabling immediate actions, the detection of wildfires has been studied with reference to the Australian events that occurred in December 2019. Convolutional neural networks (CNNs) were developed, trained, and used from the ground up to detect wildfires while also adjusting their complexity to meet onboard implementation requirements for trusted autonomous satellite operations (TASO). The capability of a 1-dimensional convolution neural network (1-DCNN) to classify wildfires is demonstrated in this research and the results are assessed against those reported in the literature. In order to enable autonomous onboard data processing, various hardware accelerators were considered and evaluated for onboard implementation. The trained model was then implemented in the following: Intel Movidius NCS-2 and Nvidia Jetson Nano and Nvidia Jetson TX2. Using the selected onboard hardware, the developed model was then put into practice and analysis was carried out. The results were positive and in favour of using the technology that has been proposed for onboard data processing to enable TASO on future missions. The findings indicate that data processing onboard can be very beneficial in disaster management and climate change mitigation by facilitating the generation of timely alerts for users and by enabling rapid and appropriate responses.

IEEE/AIAA 41st Digital Avionics Systems Conference (DASC)

Satellite technologies are used for both civil and military purposes in the modern world, and typ... more Satellite technologies are used for both civil and military purposes in the modern world, and typical applications include Communication, Navigation and Surveillance (CNS) services, which have a direct impact several economic, social and environmental protection activity. The increasing reliance on satellite services for safety-of-life and mission-critical applications (e.g., transport, defense and public safety services) creates a severe, although often overlooked, security problem, particularly when it comes to cyber threats. Like other increasingly digitized services, satellites and space platforms are vulnerable to cyberattacks. Thus, the existence of cybersecurity flaws may pose major threats to space-based assets and associated key infrastructure on the ground. These dangers could obstruct global economic progress and, by implication, international security if they are not properly addressed. Mega-constellations make protecting space infrastructure from cyberattacks much more difficult. This emphasizes the importance of defensive cyber countermeasures to minimize interruptions and ensure efficient and reliable contributions to critical infrastructure operations. Very importantly, space systems are inherently complex Cyber-Physical System (CPS) architectures, where communication, control and computing processes are tightly interleaved, and associated hardware/software components are seamlessly integrated. This represents a new challenge as many known physical threats (e.g., conventional electronic warfare measures) can now manifest their effects in cyberspace and, vice-versa, some cyber-threats can have detrimental effects in the physical domain. The concept of cyberspace underlies nearly every aspect of modern society's critical activities and relies heavily on critical infrastructure for economic advancement, public safety and national security. Many governments have expressed the desire to make a substantial contribution to secure cyberspace and are focusing on different aspects of the evolving industrial ecosystem, largely under the impulse of digital transformation and sustainable development goals. The level of cybersecurity attained in this framework is the sum of all national and international activities implemented to protect all actions in the cyber-physical ecosystem. This paper focuses on cybersecurity threats and vulnerabilities in various segments of space CPS architectures. More specifically, the paper identifies the applicable cyber threat mechanisms, conceivable threat actors and the associated space business implications. It also presents metrics and strategies for countering cyber threats and facilitating space mission assurance.

IEEE/AIAA 41st Digital Avionics Systems Conference (DASC), 2022

In this paper, we propose a rerouting method based on hybrid Artificial Intelligence (AI) algorit... more In this paper, we propose a rerouting method based on hybrid Artificial Intelligence (AI) algorithms for managing Unmanned Aircraft Systems (UAS) and Urban Air Mobility (UAM) traffic during their cruise and approach phases. The adopted approach capitalizes upon Four-Dimensional Trajectory (4DT) functionalities, supporting an uncertainty-resilient and flexible strategic deconfliction framework to improve the operational efficiency and security of Demand-Capacity Balancing (DCB) services. The objective is to accommodate future UAM and other autonomous vehicle-based business models by safely implementing traffic management in dense low-altitude airspace around cities and suburbs. The proposed UAS Traffic Management (UTM) system uses metaheuristic algorithm, especially the Tabu-search algorithm, to determine a global optimised rerouting solution. The calculated solutions can be continuously used as labelled data to train and optimise a machine learning process for real-time decision making, greatly improving the computational performance of intelligent UTM systems.

Progress in Aerospace Sciences, 2021

Integrated System Health Management (ISHM) is a promising technology that fuses sensor data and h... more Integrated System Health Management (ISHM) is a promising technology that fuses sensor data and historical state-of-health information of components and subsystems to provide actionable information and enable intelligent decision-making regarding the operation and maintenance of aerospace systems. ISHM fundamentally relies on assessments and predictions of system health, including the early detection of failures and estimation of Remaining Useful Life (RUL). Model-based, data-driven or hybrid reasoning techniques can be utilized to maximise the timeliness and reliability of diagnosis and prognosis information. The benefits of ISHM include enhancing the maintainability, reliability, safety and performance of systems. The next evolution of the ISHM concept, Intelligent Health and Mission Management (IHMM), delves deeper into the utilization of on-line system
health predictions to modify mission profiles to ensure safety and reliability, as well as efficiency through predictive integrity. This concept is particularly important for Trusted Autonomous System (TAS) applications, where an accurate assessment of the current and future system state-of-health to make operational decisions (with or without human intervention) is integral to both flight safety and mission success. IHMM systems introduce the capability of predicting degradation in the functional performance of subsystems, with sufficient time to dynamically identify which appropriate restorative or reconfiguration actions to take in order to ensure that the system can perform at an acceptable level of operational capability before the onset of a failure event. This paper reviews some of the key advancements and contributions to knowledge in the field of ISHM for the aerospace industry, with a particular focus on various architectures and reasoning strategies involving the use of artificial intelligence. The paper also discusses the key challenges faced in the development and deployment of ISHM systems in the aerospace industry and highlights the safety-critical role that IHMM will play in future cyber-physical and autonomous system applications (both vehicle and ground support systems), such as Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Urban Air Mobility (UAM) and Distributed Satellite Systems (DSS).

Future aviation research in Australia: addressing air transport safety, efficiency and environmental sustainability

International Journal of Sustainable Aviation

Avionics-based GNSS integrity augmentation synergies with SBAS and GBAS for safety-critical aviation applications

2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC), 2016

This paper explores the synergies between a novel Global Navigation Satellite System (GNSS) Avion... more This paper explores the synergies between a novel Global Navigation Satellite System (GNSS) Avionics-Based Integrity Augmentation (ABIA) system and current Space and Ground Based Augmentation Systems (SBAS and GBAS). The ABIA Integrity Flag Generator (IFG) is designed to provide caution and warning integrity flags (in accordance with the specified time-to-caution and time-to-warning requirements) in all relevant flight phases. The ABIA IFG performances are assessed and compared with the SBAS and GBAS integrity flag generation capability. Simulation case studies are presented using the TORNADO-IDS platform and they provide insights on possible mutual benefits attainable by integrating ABIA with SBAS and GBAS systems. The results show that the proposed integrated scheme is capable of performing high-integrity tasks when GNSS is used as the primary source of navigation data. Furthermore, it is evident that there is a clear synergy of ABIA with SBAS and GBAS in providing suitable (predictive and reactive) integrity flags in all flight phases. The integration is thus a clear opportunity for future research towards the development of a Space-Ground-Avionics Augmentation Network (SGAAN) for a number of safety-critical aviation applications.

An evolutionary outlook of air traffic flow management techniques

Progress in Aerospace Sciences, 2016

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.

A low-cost and high performance navigation system for small RPAS applications

Aerospace Science and Technology, 2016

Modern Remotely Piloted Aircraft Systems (RPAS) employ a variety of sensors and multi-sensor data... more Modern Remotely Piloted Aircraft Systems (RPAS) employ a variety of sensors and multi-sensor data fusion techniques to provide advanced functionalities and trusted autonomy in a wide range of mission-essential and safety-critical tasks. In particular, Navigation and Guidance Systems (NGS) for small RPAS require a typical combination of lightweight, compact and inexpensive sensors to satisfy the Required Navigation Performance (RNP) in all flight phases. In this paper, the synergies attainable by the combination of Global Navigation Satellite System (GNSS), Micro-Electromechanical System based Inertial Measurement Unit (MEMS-IMU) and Vision-Based Navigation (VBN) sensors are explored. In case of VBN, an appearance-based navigation technique is adopted and feature extraction/optical flow methods are employed to estimate the navigation parameters during precision approach and landing phases. A key novelty of the proposed approach is the employment of Aircraft Dynamics Models (ADM) augmentation to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. To obtain the best estimates of Position, Velocity and Attitude (PVA), different sensor combinations are analysed and dynamic Boolean Decision Logics (BDL) are implemented for data selection before the centralised data fusion is accomplished. Various alternatives for data fusion are investigated including a traditional Extended Kalman Filter (EKF) and a more advanced Unscented Kalman Filter (UKF). A novel hybrid controller employing fuzzy logic and Proportional-Integral-Derivative (PID) techniques is implemented to provide effective stabilization and control of pitch and roll angles. After introducing the key mathematical models describing the three NGS architectures: EKF based VBN-IMU-GNSS (VIG) and VBN-IMU-GNSS-ADM (VIGA) and UKF based Enhanced VIGA (EVIGA), the system performances are compared in a small RPAS integration scheme (i.e., AEROSONDE RPAS platform) exploring a representative cross-section of the aircraft operational flight envelope. A dedicated ADM processor (i.e., a local pre-filter) is adopted in the EVIGA architecture to account for the RPAS maneuvering envelope in different flight phases (assisted by a maneuver identification algorithm), in order to extend the ADM validity time across all segments of the RPAS trajectory. Simulation results show that the VIG, VIGA and EVIGA systems are compliant with ICAO requirements for precision approach down to CAT-II. In all other flight phases, the VIGA system shows improvement in PVA data output with respect to the VIG system. The EVIGA system shows the best performance in terms of attitude data accuracy and a significant extension of the ADM validity time is achieved in this configuration.

Aircraft dynamics model augmentation for RPAS navigation and guidance

2016 International Conference on Unmanned Aircraft Systems (ICUAS), 2016

In this paper, Aircraft Dynamics Model (ADM) augmentation for Remotely Piloted Aircraft System (R... more In this paper, Aircraft Dynamics Model (ADM) augmentation for Remotely Piloted Aircraft System (RPAS) navigation and guidance is presented. This approach provides additional information suitable to compensate for the shortcomings of vision based navigation sensors and Micro-Electromechanical System Inertial Measurement Unit (MEMS-IMU) sensors for attitude determination tasks. The ADM virtual sensor is essentially a knowledge-based module and is used to augment the navigation state vector by predicting RPAS flight dynamics (aircraft trajectory and attitude motion). The ADM employs a rigid body 6-Degree of Freedom (6-DoF) model and is implemented in integrated multi-sensor data fusion architectures. The integration is accomplished with an Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). After introducing the key mathematical models describing the 6-DoF ADM, the sensor and integrated system performance are compared in a small RPAS integration scheme (i.e., AEROSONDE RPAS platform) exploring a representative cross-section of the aircraft operational flight envelope and a preliminary sensitivity analysis is performed. In addition to a centralised filter, a dedicated ADM processor (i.e., a local pre-filter) is adopted to account for the RPAS manoeuvring envelope in different flight phases, in order to extend the ADM validity time across all segments of the RPAS trajectory. Sensitivity analysis of the errors caused by perturbations in the input parameters of the aircraft dynamics is performed to demonstrate the robustness of the proposed approach. Results verify that the ADM virtual sensor provides improved performance in terms of attitude data accuracy and a significant extension of the ADM validity time is achieved by pre-filtering.

A Laser Obstacle Detection and Collision Avoidance System for Small Unmanned Aerial Vehicle Applications

High Precision Global Positioning System (GPS) for Flight Testing

ABSTRACT Historically, test ranges have provided accurate time and space position information (TS... more ABSTRACT Historically, test ranges have provided accurate time and space position information (TSPI) by using laser tracking systems, kinetheodolite systems, tracking radars, and ground-based radio positioning systems. These systems have a variety of limitations. In general, they provide a TSPI solution based on measurements relative to large and costly fixed ground stations. Weather has an adverse effect on many of these systems, and all of them are limited to minimum altitudes or confined geographic regions. The Global Positioning System (GPS) provides a cost-effective capability that overcomes nearly all the limitations of existing TSPI sources. GPS is a passive system using satellites, which provides universal and accurate source of real-time position, and timing data to correlate mission events. The coverage area is unbounded and the number of users is unlimited. The use of land-based differential GPS (DGPS) reference stations improves accuracy to about one meter for relatively stationary platforms, and to a few meters for high performance tactical aircraft. Further accuracy enhancement can be obtained by using GPS carrier phase measurements, either in post-processing or in real-time. Accuracy does not degrade at low altitudes above the earth’s surface, and loss of navigation solution does not occur as long as the antenna has an open view of the sky. Therefore, it was important to undertake a study in order to investigate the range of possible applications of DGPS in the flight test environment, taking also into account possible integration (in real-time and in post-processing) with other systems. In this AGARDograph, the potential of DGPS as a positioning datum for flight test applications is deeply discussed. Current technology status and future trends are investigated in order to identify optimal system architectures for both the on-board and ground station components, and to define optimal strategies for DGPS data gathering during various flight testing tasks. Limitations of DGPS techniques are deeply analyzed, and various possible integration schemes with other sensors are considered. Finally, the architecture of an integrated position reference system suitable for flight test applications is identified. The purpose of this AGARDograph is to provide comprehensive guidance on assessing the need for and determining the characteristics of DGPS based position reference systems for flight test activities. The specific goals are to make available to the NATO flight test community the best practices and advice for DGPS based systems architecture definition and equipment selection. A variety of flight test applications are examined and both real-time and post-mission DGPS data requirements are outlined. Particularly, DGPS accuracy, continuity and integrity issues are considered, and possible improvements achievable by means of signal augmentation strategies are identified. Possible architectures for integrating DGPS with other airborne sensors (e.g., INS, Radalt) are presented, with particular emphasis on current and likely future data fusion algorithms. Particular attention is devoted to simulation analysis in support of flight test activities with DGPS. Finally, an outline of current research perspectives in the field of DGPS technology is given.

Minimizing the Cost of Weather Cells and Persistent Contrail Formation Region Avoidance Using Multi-Objective Trajectory Optimization in Air Traffic Management

SAE International Journal of Aerospace, 2015

A Novel Approach to Cooperative and Non-Cooperative RPAS Detect-and-Avoid

SAE Technical Paper Series, 2015

A Laser Obstacle Avoidance System for Helicopter Nap-of-the-Earth Flying