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Aerospace
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Avionic Systems
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Avionic Systems

A topical collection in Aerospace (ISSN 2226-4310).

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Editors

Dr. Carlos Insaurralde

E-Mail Website
Collection Editor
Bristol Robotics Laboratory, University of the West of England, Bristol BS16 1QY, UK
Interests: multidisciplinary development of high-integrity systems; architectures of intelligent and autonomous systems; metric assessment of systems performance.
Prof. Dr. Francesco Dell’Olio

E-Mail Website
Co-Collection Editor
Department of Electrical and Information Engineering, Polytechnic University of Bari, 70126 Bari, Italy
Interests: photonics; optoelectronics; sensors; chemosensors
Special Issues, Collections and Topics in MDPI journals

Topical Collection Information

Dear Colleagues,

Avionic systems have undergone remarkable technological investigation and innovation in the last 50 years. The inexorable evolution involves updates and upgrades on two main branches of avionics: Communication, Navigation, and Surveillance (CNS) and Guidance, Navigation, and Control (GNC). CNS entails avionic engineering of enabling systems for aircraft and spacecraft operations, such as air traffic control and space mission control. GNC focuses on air and space vehicles themselves regarding movement performance, such as vehicle flight control.

The development and advancement of avionic CNS/GNC systems involve solutions for a range of applications for substantiable air/space transportation, e.g., management of air/space traffic, including integration of unmanned systems and the use of intelligent satellites. Avionic approaches require considerations of aspects regarding safety and security (including cybersecurity), as well as standards and certification of avionic systems. Evolutionary architectures of avionic systems take great progress on automation to the next level and foster autonomy. This step forward pushes technological solutions beyond avionics and involves other disciplines, such as robotics and Artificial Intelligence.

This Special Issue is aimed at the dissemination of research and engineering advances on avionic systems for CNS and GNC, including challenges and opportunities for current and future avionics for aeronautics and astronautics. Topics and areas of the Special Issue include but are not limited to:

  • Application of Artificial Intelligence in avionic systems;
  • Robotic avionics and autonomous avionics for air/space vehicles;
  • Smart CNS avionics for airspace/space integration of unmanned systems;
  • Connectivity and cybersecurity certification of avionic systems;
  • Human–avionics collaboration for augmented intelligence;
  • Distributed integrated modular avionics and future avionics architectures and networks;
  • Reconfigurable GNS avionics for next generations of air/space transport;
  • Intelligent satellite constellation and radar satellites;
  • Avionics power management and distribution;
  • Cyber-physical avionics systems.

Dr. Carlos Insaurralde
Dr. Francesco Dell’Olio
Collection Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Aerospace is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (9 papers)

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2024

Jump to: 2023, 2022

33 pages, 16970 KiB  
Article
Ontological Airspace-Situation Awareness for Decision System Support
by Carlos C. Insaurralde and Erik Blasch
Aerospace 2024, 11(11), 942; https://doi.org/10.3390/aerospace11110942 - 15 Nov 2024
Viewed by 636
Abstract
Air Traffic Management (ATM) has become complicated mainly due to the increase and variety of input information from Communication, Navigation, and Surveillance (CNS) systems as well as the proliferation of Unmanned Aerial Vehicles (UAVs) requiring Unmanned Aerial System Traffic Management (UTM). In response [...] Read more.
Air Traffic Management (ATM) has become complicated mainly due to the increase and variety of input information from Communication, Navigation, and Surveillance (CNS) systems as well as the proliferation of Unmanned Aerial Vehicles (UAVs) requiring Unmanned Aerial System Traffic Management (UTM). In response to the UTM challenge, a decision support system (DSS) has been developed to help ATM personnel and aircraft pilots cope with their heavy workloads and challenging airspace situations. The DSS provides airspace situational awareness (ASA) driven by knowledge representation and reasoning from an Avionics Analytics Ontology (AAO), which is an Artificial Intelligence (AI) database that augments humans’ mental processes by means of implementing AI cognition. Ontologies for avionics have also been of interest to the Federal Aviation Administration (FAA) Next Generation Air Transportation System (NextGen) and the Single European Sky ATM Research (SESAR) project, but they have yet to be received by practitioners and industry. This paper presents a decision-making computer tool to support ATM personnel and aviators in deciding on airspace situations. It details the AAO and the analytical AI foundations that support such an ontology. An application example and experimental test results from a UAV AAO (U-AAO) framework prototype are also presented. The AAO-based DSS can provide ASA from outdoor park-testing trials based on downscaled application scenarios that replicate takeoffs where drones play the role of different aircraft, i.e., where a drone represents an airplane that takes off and other drones represent AUVs flying around during the airplane’s takeoff. The resulting ASA is the output of an AI cognitive process, the inputs of which are the aircraft localization based on Automatic Dependent Surveillance–Broadcast (ADS-B) and the classification of airplanes and UAVs (both represented by drones), the proximity between aircraft, and the knowledge of potential hazards from airspace situations involving the aircraft. The ASA outcomes are shown to augment the human ability to make decisions. Full article
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18 pages, 9176 KiB  
Article
A Non-Contact AI-Based Approach to Multi-Failure Detection in Avionic Systems
by Chengxin Liu, Michele Ferlauto and Haiwen Yuan
Aerospace 2024, 11(11), 864; https://doi.org/10.3390/aerospace11110864 - 22 Oct 2024
Viewed by 922
Abstract
The increasing electrification and integration of advanced controls in modern aircraft designs have significantly raised the number and complexity of installed printed circuit boards (PCBs), posing new challenges for efficient maintenance and rapid failure detection. Despite self-diagnostic features in current avionics systems, circuit [...] Read more.
The increasing electrification and integration of advanced controls in modern aircraft designs have significantly raised the number and complexity of installed printed circuit boards (PCBs), posing new challenges for efficient maintenance and rapid failure detection. Despite self-diagnostic features in current avionics systems, circuit damage and multiple simultaneous failures may arise, compromising safety and diagnostic accuracy. To address these challenges, this paper aims to develop a fast, accurate, and non-destructive, multi-failure diagnosis algorithm for PCBs. The proposed method combines a self-attention mechanism with an adaptive graph convolutional neural network to enhance diagnostic precision. A convolutional neural network with residual connections extracts features from scalar magnetic field data, ensuring robust input diversity. The model was tested on a typical dual-phase amplitude boosting circuit with up to four different simultaneous failures, achieving the experimental results of 99.08%, 98.50%, 98.78%, 98.01%, 98.93%, 98.25%, 97.03%, and 99.77% across metrics including overall precision, per-class precision, overall recall, per-class recall, overall F1 measure, and per-class F1 measure. The results demonstrated its effectiveness and feasibility in diagnosing complex PCBs with multiple failures, indicating the algorithm’s potential to improve failure diagnosis performance and offer a promising PCB diagnosis solution in aerospace applications. Full article
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20 pages, 5181 KiB  
Article
Resource Allocation Approach of Avionics System in SPO Mode Based on Proximal Policy Optimization
by Lei Dong, Jiachen Liu, Zijing Sun, Xi Chen and Peng Wang
Aerospace 2024, 11(10), 812; https://doi.org/10.3390/aerospace11100812 - 4 Oct 2024
Viewed by 1086
Abstract
Single-Pilot Operations (SPO) mode is set to reshape the decision-making process between human-machine and air-ground operations. However, the limited on-board computing resources impose greater demands on the organization of performance parameters and the optimization of process efficiency in SPO mode. To address this [...] Read more.
Single-Pilot Operations (SPO) mode is set to reshape the decision-making process between human-machine and air-ground operations. However, the limited on-board computing resources impose greater demands on the organization of performance parameters and the optimization of process efficiency in SPO mode. To address this challenge, this paper first investigates the flexible requirements of avionics systems arising from changes in SPO operational scenarios, then analyzes the architecture of Reconfigurable Integrated Modular Avionics (RIMA) and its resource allocation framework in the context of scarcity and configurability. A “mission-function-resource” mapping relationship is established between the reconfiguration service elements of SPO mode and avionics resources. Subsequently, the Proximal Policy Optimization (PPO) algorithm is introduced to simulate the resource allocation process of IMA reconfiguration in SPO mode. The objective optimization process is transformed into a sequential decision-making problem by considering constraints and optimization criteria such as load, latency, and power consumption within the feasible domain of avionics system resources. Finally, the resource allocation scheme for avionics system reconfiguration is determined by controlling the probability of action selection during the interaction between the agent and the environment. The experimental results show that the resource allocation scheme based on the PPO algorithm can effectively reduce power consumption and latency, and the DRL model has strong anti-interference and generalization. This enables avionics resources to respond dynamically to the capabilities required in SPO mode and enhances their ability to support the aircraft mission at all stages. Full article
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2023

Jump to: 2024, 2022

27 pages, 6628 KiB  
Article
Incipient Fault Detection and Reconstruction Using an Adaptive Sliding-Mode Observer for the Actuators of Fixed-Wing Aircraft
by Lina Wang, Wen Zhao, Zhenbao Liu, Qingqing Dang, Xu Zou and Kai Wang
Aerospace 2023, 10(5), 422; https://doi.org/10.3390/aerospace10050422 - 29 Apr 2023
Viewed by 1643
Abstract
This paper proposes a new method of detection and reconstruction of the incipient fault of fixed-wing actuators based on an adaptive sliding-mode observer. First, a mathematical model of a fixed-wing aircraft is derived under certain assumptions, considering nonlinear terms and system disturbances. Second, [...] Read more.
This paper proposes a new method of detection and reconstruction of the incipient fault of fixed-wing actuators based on an adaptive sliding-mode observer. First, a mathematical model of a fixed-wing aircraft is derived under certain assumptions, considering nonlinear terms and system disturbances. Second, by introducing a nonsingular coordinate transformation, the incipient faults are separated from the disturbances. For a subsystem with no disturbances, the Luenberger observer can estimate the incipient fault. For a subsystem with disturbances, the sliding-mode observer is robust against these disturbances. The Lyapunov stability theory guarantees dynamic error convergence and system stability. The evaluation function was designed to realize residual evaluation and threshold judgment. Third, based on the concept of equivalent output injection, an adaptive sliding-mode observer method is proposed to reconstruct actuator faults precisely under the condition of the uncertain system structure. The design steps of the proposed reconstruction method are introduced in the form of a linear matrix inequality problem, which provides an effective method for calculating the design parameters. Finally, the simulation results of the De Havilland DHC-2 “Beaver” aircraft demonstrate the correctness and effectiveness of the proposed method. Full article
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12 pages, 493 KiB  
Communication
Angle-of-Attack Estimation for General Aviation Aircraft
by Marin Ivanković, Milan Vrdoljak, Marijan Andrić and Hrvoje Kozmar
Aerospace 2023, 10(3), 315; https://doi.org/10.3390/aerospace10030315 - 22 Mar 2023
Cited by 1 | Viewed by 2462
Abstract
The angle of attack is one of the most important flight parameters. In the framework of the present study, a flight data recording method was designed to analyze the Valasek angle-of-attack estimation method and investigate its applicability for general aviation aircraft. This was [...] Read more.
The angle of attack is one of the most important flight parameters. In the framework of the present study, a flight data recording method was designed to analyze the Valasek angle-of-attack estimation method and investigate its applicability for general aviation aircraft. This was performed using two devices characterized by substantially different characteristics. The test flight, and the ground test, i.e., a flight simulator experiment, were conducted. Two flight regimes were analyzed: (a) steady climb and descent with low values of angle of attack, (b) approach to stall with idle power with an increase of the angle of attack to the critical value. A satisfactory angle of attack estimate was obtained for the steady climb and descent regime, while the approach to stall estimate was less accurate but still indicative and considered useful for the pilot. The results indicate that less expensive synthetic sensors may provide acceptable results compared to high-quality certified equipment. A proposed modification of the estimation method enables simplification of the required equipment, while offering important information to the pilot. Full article
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16 pages, 7082 KiB  
Article
RAMSEES: A Model of the Atmospheric Radiative Environment Based on Geant4 Simulation of Extensive Air Shower
by Hugo Cintas, Frédéric Wrobel, Marine Ruffenach, Damien Herrera, Frédéric Saigné, Athina Varotsou, Françoise Bezerra and Julien Mekki
Aerospace 2023, 10(3), 295; https://doi.org/10.3390/aerospace10030295 - 16 Mar 2023
Cited by 5 | Viewed by 2152
Abstract
The device downscaling of electronic components has given rise to the need to consider specific failures in onboard airplane electronics. Single Event Effects (SEE) are a kind of failures that occur due to radiation in the atmosphere. For the purpose of ensuring onboard [...] Read more.
The device downscaling of electronic components has given rise to the need to consider specific failures in onboard airplane electronics. Single Event Effects (SEE) are a kind of failures that occur due to radiation in the atmosphere. For the purpose of ensuring onboard electronic reliability, there is a clear need for new tools to predict the SEE rate, at both avionic altitudes and at ground level. In this work, we develop a new tool: RAMSEES (Radiation Atmospheric Model for SEE Simulation), which simulates the atmospheric radiative environment induced by cosmic rays. This multiscale and multi-physics phenomenon is simulated using the Geant4 toolkit, allowing the creation of a database to characterize the radiation environment in the atmosphere as a function of altitude. We show the need to simulate very high-energy particles such as 100 TeV space protons, because they are the main contributor of radiation at avionic altitudes as well as at ground level. Our approach shows a good agreement with the experimental data, the standards, and other models, and it also points out some discrepancies, especially below 18 km of altitude. RAMSEES can be the basis of the estimation of the SEE rate from ground level to the stratosphere, at any given position and time. Full article
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21 pages, 7920 KiB  
Article
An Efficient Task Synthesis Method Based on Subspace Differential Patterns for Arrangements of Event Intervals Mining in the Avionics Cloud System Architecture
by Xiaoxu Dong, Xin Wang, Ling Peng, Miao Wang and Guoqing Wang
Aerospace 2023, 10(3), 249; https://doi.org/10.3390/aerospace10030249 - 5 Mar 2023
Viewed by 1623
Abstract
Avionics Cloud is a new multi-platform avionics system architecture that provides dynamic access, resource pooling, intelligent scheduling, on-demand service and other cloud computing features. Using Avionics Cloud to rationalize the order of multi-flight platform task execution and realize multitask synthesis is a challenging [...] Read more.
Avionics Cloud is a new multi-platform avionics system architecture that provides dynamic access, resource pooling, intelligent scheduling, on-demand service and other cloud computing features. Using Avionics Cloud to rationalize the order of multi-flight platform task execution and realize multitask synthesis is a challenging problem. In this paper, we propose an Efficient Task Synthesis Method based on Subspace Differential Patterns for Arrangements of Event Intervals Mining-DiMining. For tasks executed in a multi-platform Avionics Cloud system with dynamic characteristics of time intervals, DiMining is proposed. The algorithm mines the differential frequent task execution event interval patterns related to execution efficiency from the scenario dataset with high execution efficiency and the scenario dataset with low execution efficiency in order to identify key task patterns related to execution efficiency and improve the task synthesis design efficiency of the multi-platform Avionics Cloud system. Furthermore, in order to improve the mining efficiency of the algorithm, this algorithm designs a variety of pruning strategies to ensure that two differential time interval patterns with high and low functional execution efficiency are mined at one time without preserving the set of candidate items. The experimental results show that the DiMining algorithm is more efficient than the traditional algorithm on the open dataset. The DiMining algorithm is used to mine the 350-field high-efficiency operation scenario dataset and the 350-field efficiency operation scenario dataset under the constructed typical UAV cluster co-detection task scenarios. Based on the simulation results, the DiMining algorithm is able to effectively support the design of multi-platform Avionics Cloud system task synthesis architecture and improve the efficiency of UAV cluster collaborative detection. Full article
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29 pages, 4508 KiB  
Article
Organization Preference Knowledge Acquisition of Multi-Platform Aircraft Mission System Utilizing Frequent Closed Itemset Mining
by Yuqian Wu, Miao Wang, Wenkui Chu and Guoqing Wang
Aerospace 2023, 10(2), 166; https://doi.org/10.3390/aerospace10020166 - 10 Feb 2023
Cited by 1 | Viewed by 1849
Abstract
Organization preference knowledge is critical to enhancing the intelligence and efficiency of the multi-platform aircraft mission system (MPAMS), particularly the collaboration tactics of task behaviors, platform types, and mount resources. However, it is challenging to extract such knowledge concisely, which is buried in [...] Read more.
Organization preference knowledge is critical to enhancing the intelligence and efficiency of the multi-platform aircraft mission system (MPAMS), particularly the collaboration tactics of task behaviors, platform types, and mount resources. However, it is challenging to extract such knowledge concisely, which is buried in massive historical data. Therefore, this paper proposes an innovative data-driven approach via frequent closed itemset mining (FCIM) algorithm to discover valuable MPAMS organizational knowledge. The proposed approach addresses the limitations of poor effectiveness and low mining efficiency for the previously discovered knowledge. To ensure the knowledge effectiveness, this paper designs a multi-layer knowledge discovery framework from the system-of-systems perspective, allowing to discover more systematic knowledge than traditional frameworks considering an isolated layer. Additionally, the MPAMS’s contextual capability reflecting the decision motivation is integrated into the knowledge representation, making the knowledge more intelligible to decision-makers. Further, to ensure mining efficiency, the knowledge mining process is accelerated by designing an itemset storage structure and three pruning strategies for FCIM. The simulation of 1100 air-to-sea assault scenarios has provided abundant knowledge with high interpretability. The performance superiority of the proposed approach is thoroughly verified by comparative experiments. The approach provides guidance and insights for future MPAMS development and organization optimization. Full article
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2022

Jump to: 2024, 2023

13 pages, 2077 KiB  
Article
Flight Speed Evaluation Using a Special Multi-Element High-Speed Temperature Probe
by Michal Schmirler
Aerospace 2022, 9(4), 185; https://doi.org/10.3390/aerospace9040185 - 31 Mar 2022
Viewed by 2145
Abstract
In the context of aircraft aerodynamics, the compressibility of air flowing around the aircraft must always be considered. This fact brings with it one inconvenience: to evaluate the velocity of the flowing air (airspeed), it is necessary to know its temperature as well. [...] Read more.
In the context of aircraft aerodynamics, the compressibility of air flowing around the aircraft must always be considered. This fact brings with it one inconvenience: to evaluate the velocity of the flowing air (airspeed), it is necessary to know its temperature as well. Unfortunately, direct measurement of the temperature of air flowing at high speed (usually at Ma > 0.3) is practically impossible without knowledge of its velocity. Thus, there are two unknown quantities in the problem that depend on each other. The solution is achieved by a method that uses temperature probes composed of multiple sensors with different properties (different recovery factors). The comparison of rendered temperatures subsequently allows the elimination of the necessary knowledge of static temperature and the evaluation of velocity. In this paper, one of such probes is described together with its thermodynamic properties and possible applications. Full article
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