Flight Test Research Articles

A Cloud Detection System for UAV Sense and Avoid: Analysis of a Monocular Approach in Simulation and Flight Tests

In order to contribute to the operation of unmanned aerial vehicles (UAVs) according to visual flight rules (VFR), this article proposes a monocular approach for cloud detection using an electro-optical sensor. Cloud avoidance is motivated by several factors, including improving visibility for collision prevention and reducing the risks of icing and turbulence. The described workflow is based on parallelized detection, tracking and triangulation of features with prior segmentation of clouds in the image. As output, the system generates a cloud occupancy grid of the aircraft’s vicinity, which can be used for cloud avoidance calculations afterwards. The proposed methodology was tested in simulation and flight experiments. With the aim of developing cloud segmentation methods, datasets were created, one of which was made publicly available and features 5488 labeled, augmented cloud images from a real flight experiment. The trained segmentation models based on the YOLOv8 framework are able to separate clouds from the background even under challenging environmental conditions. For a performance analysis of the subsequent cloud position estimation stage, calculated and actual cloud positions are compared and feature evaluation metrics are applied. The investigations demonstrate the functionality of the approach, even if challenges become apparent under real flight conditions.

Optimal Task Allocation and Sequencing for Flight Test Based on a Memetic Algorithm With Lexicographic Optimisation

ABSTRACTThe flight test plays an important role in the development of an aircraft. Currently, with the increasing complexity and higher validation requirements for aircraft, there is a crucial need to generate high‐quality flight test task schedules in an efficient way. This paper proposes a flight test task scheduling problem (FTTSP), which involves assigning suitable aircraft and executing the flight test tasks in a given order. Generally, the flight test duration (FTD) is the primary optimisation objective for the flight test task schedule, as it has a direct impact on aircraft development costs and the time to enter the market. In this study, the FTTSP not only considers FTD but also takes into account task transfer consumption (TTC). A mixed‐integer linear programming mathematical model is first formulated to describe the FTTSP characteristics with the optimisation of the FTD and the TTC in a sequential manner. Then, a memetic algorithm with lexicographic optimisation (MALO) is proposed, which can efficiently obtain a high‐quality solution and ensure that the most critical metric can be fully optimised. In MALO, a two‐vector encoding and a task logic relationship repair mechanism based on the binary tree are established. An idle time insertion decoding method is designed to improve the aircraft utilisation rate. In addition to the selection, crossover and mutation operators, a local search operator is designed to enhance the solution quality. Finally, the full‐scale test instances are generated for the FTTSP to evaluate the algorithm's performance. The numerical results demonstrate the effectiveness and competitiveness of the MALO in generating a high‐quality schedule for flight test tasks.

Application of Deep Learning to Identify Flutter Flight Testing Signals Parameters and Analysis of Real F-18 Flutter Flight Test Data

Application of Deep Learning to Identify Flutter Flight Testing Signals Parameters and Analysis of Real F-18 Flutter Flight Test Data

Autonomous Landing of a Fixed‐Wing UAV With RTK GNSS and MEMS IMU

Autonomous landing system is an important part of unmanned aerial vehicle (UAV) autonomous flight. Large fixed‐wing UAVs often consume more onboard space and computing resources. With the improvement of system integration and the reduction of high‐performance global navigation satellite system (GNSS) costs, real‐time kinematic (RTK) GNSS has been widely used in small‐scale and low‐cost fixed‐wing UAVs. This article uses less onboard hardware and ground facility requirements to design an autonomous taking off and landing system suitable for general fixed‐wing UAVs. A modified gradient descent attitude estimator, based on microelectromechanical system (MEMS) inertial measurement unit (IMU) and RTK GNSS, and a guidance method based on a tracking differentiator for using in a high dynamic environment are proposed, and circular path following and vertical transient simulations are performed. The simulation results show that this method can improve attitude estimation accuracy, motion control accuracy, and altitudinal transient quality. Finally, the actual flight test verifies its feasibility in the actual environment. The flight test results prove that it is feasible to implement the autonomous landing process of fixed‐wing UAV with the proposed system and method.

Research on airworthiness verification technology of minimum weight MOC8 test of civil aircraft

Research on airworthiness verification technology of minimum weight MOC8 test of civil aircraft

Design and research of real-time monitoring software for IFTD flight test of civil aircraft

Design and research of real-time monitoring software for IFTD flight test of civil aircraft

Research on airworthiness verification technology of handling quality after control surface malfunction MOC8 test of civil aircraft

Research on airworthiness verification technology of handling quality after control surface malfunction MOC8 test of civil aircraft

Research on flight test method and optimization strategy for takeoff and landing performance of civil aircraft

Research on flight test method and optimization strategy for takeoff and landing performance of civil aircraft

Adaptive velocity control for UAV boat landing: A neural network and particle swarm optimization approach

Achieving precise landing of Unmanned Aerial Vehicles (UAVs) onto moving platforms, such as Autonomous Surface Vehicles (ASVs), is challenging, particularly in GPS-denied environments with dynamic disturbances. Conventional methods often rely on high-level waypoint navigation, extensive manual tuning, and expensive sensors. In this work, we propose an adaptive Proportional-Integral-Derivative (PID) controller optimization using a Neural Network-Particle Swarm Optimization (NN-PSO) algorithm. The algorithm dynamically tunes the PID controller, significantly reducing manual tuning effort, while relying solely on a low-cost camera and altitude sensor. The NN-PSO algorithm allows the UAV to land with an average error of 5 cm on static platforms and 10 cm on moving boats, based on multiple test flights. Our method also increases the maximum landing speed to 80.9% of the UAV’s top flight speed, a considerable improvement over existing systems. Our approach not only optimizes landing precision but also introduces techniques for ensuring soft landings, reducing oscillations, and preventing target misses. These enhancements make the method robust across varying flight altitudes and ASV speeds. Furthermore, this approach is applicable to a variety of GPS-denied scenarios, including rescue missions, package deliveries, and workspace inspections, without requiring costly equipment or extensive parameter tuning. Field experiments confirm the precision and stability of the proposed system, validating its performance in real-world conditions. [Video]

Investigation of Energy-Maneuverability Methods for Helicopter Performance Assessments

Energy-maneuverability diagrams are an important tool that operational pilots use to understand helicopter maneuver performance through excess available power across a wide range of conditions. These representations are based upon a number of assumptions that have not been rigorously investigated for helicopter applications. The present work reports the results of an investigation into the theory and application of helicopter maneuverability through simulation and flight test. The computational portion of the work focused on a systematic investigation into some of the key simplifying assumptions that are commonly applied in the creation of energy-maneuverability diagrams using two rotor wake aerodynamic modeling methods. The flight test portion of the work provided important operational context for understanding the practical application of the simulation results. The study illustrated that the fundamental assumption employed in estimating maneuver power requirements for energy-maneuverability representations appears to be reasonable in conditions of the greatest practical relevance; however, another key assumption that is invoked to convert excess power into climb performance would likely lead to overestimating the vehicle capability in important operational conditions. Additionally, the flight test data demonstrated that, at high angles of bank, energy-maneuverability results should be considered for trending information rather than for detailed climb performance values.

Investigation of propeller configuration effects on the flight stability of unmanned aerial vehicles

This study investigates the flight stability of unmanned aerial vehicles (UAVs) by comparing two-, three-, and six-blade propellers. The experiment uses a self-made drone with a 3D-printed polylactic acid (PLA) frame and an Arduino-based flight control system to create an efficient UAV prototype. The flight tests are conducted in a controlled environment, eliminating flight confounders such as wind and temperature, and the three types of propellers are of similar size. Stability was assessed by measuring deviations in the drone’s X and Y axes while hovering within ±30 degrees, and standard deviation (SD) was calculated to quantify variability. The tests revealed that propeller count significantly impacts stability and overall performance. The three-blade propeller provided the best stability, with the smallest SD in the X-axis at 10.85 and Y-axis at 11.85, and showed the least deviation over ±30 degrees during take-off and flight. While the 2-blade propeller has the least stability in flight, with a value of 15.08 in the X-axis and 16.3 in the Y-axis, showing a deviation exceeding ±30 degrees several times throughout the test, the 6-blade propeller demonstrates intermediate performance, with a value of 12.71 in the X-axis and 15.57 in the Y-axis, which is more stable than the 2-blade propeller but still less stable than the 3-blade propeller. The results of this study provide UAV design data by studying the factors in selecting propellers with different numbers of blades for drones, presenting information on the importance of propeller selection for drone flight performance and stability. The results of this study can be applied to various drone applications, such as aerial photography, agriculture, or industry. Finally, in the future, other factors are expected to affect the differences in the number of blades regarding energy efficiency and flight duration.

Multiple-input, multiple-output modal testing of a Hawk T1A aircraft: a new full-scale dataset for structural health monitoring

The use of measured vibration data from structures has a long history of enabling the development of methods for inference and monitoring. In particular, applications based on system identification and structural health monitoring have risen to prominence over recent decades and promise significant benefits when implemented in practice. However, significant challenges remain in the development of these methods. The introduction of realistic, full-scale datasets will be an important contribution to overcoming these challenges. This article presents a new benchmark dataset capturing the dynamic response of a decommissioned BAE Systems Hawk T1A. The dataset reflects the behaviour of a complex structure with a history of service that can still be tested in controlled laboratory conditions, using a variety of known loading and damage simulation conditions. As such, it provides a key stepping stone between simple laboratory test structures and in-service structures. In this article, the Hawk structure is described in detail, alongside a comprehensive summary of the experimental work undertaken. Following this, key descriptive highlights of the dataset are presented, before a discussion of the research challenges that the data present. Using the dataset, non-linearity in the structure is demonstrated, as well as the sensitivity of the structure to damage of different types. The dataset is highly applicable to many academic enquiries and additional analysis techniques which will enable further advancement of vibration-based engineering techniques.

Forced Landing Flight Test of Compound-Wing UAVs Based on Proportional Guidance

With the development of the low-altitude economy, the demand for low-altitude flight missions has steadily increased. However, such flights often encounter special circumstances requiring emergency landings. To address this, a forced landing guidance law is designed in this paper, using a small compound-wing aircraft as the research object and based on proportional guidance principles. The guidance law calculates lateral and longitudinal acceleration commands using azimuth and elevation angles provided by a seeker, which are then input into the inner-loop control law to generate control surface commands. These commands guide the aircraft toward a nearby landing point. Hardware-in-the-loop simulations demonstrate the effectiveness and robustness of the proposed guidance law, and flight tests further validate its practical applicability.

An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning

Maritime activities have become increasingly frequent with the deepening of economic globalization, highlighting the burgeoning significance of maritime rescue. However, in practical applications, UAVs for maritime rescue face numerous challenges, such as limited endurance and inadequate autonomous planning capabilities. To optimize flight routes and circumvent adverse sea conditions, an improved Pied Kingfisher Optimizer (IPKO) that incorporates refraction reverse learning, variable spiral search, and Cauchy mutation strategies was proposed. Comparative experiments conducted on CEC2005 and CEC2022 datasets with seven traditional algorithms demonstrate that the proposed algorithm exhibits superior precision and convergence speed. Subsequently, a path planning objective function was constructed based on trajectory cost and threat cost to simulate a 3D space for UAV maritime rescue missions, and the IPKO algorithm was applied to address the UAV path planning problem. The results showed that the total cost incurred by the IPKO algorithm decreased by 5.77% compared to the PKO algorithm and by 51.19% compared to the SCA algorithm. Finally, through UAV flight tests validating its practical applicability, it is ascertained that IPKO can enhance rescue efficiency in complex maritime rescue environments.

Design and Modeling of a High-Peak-Power Distributed Electric Propulsion System for a Super-STOL UAV

Electric short takeoff and landing (eSTOL) aircraft utilize the slipstream generated by distributed propellers to significantly increase the effective lift coefficient and reduce the takeoff and landing distances. By utilizing the blown lift, eSTOL UAVs can achieve similar takeoff and landing site requirements as electric vertical takeoff and landing (eVTOL) UAVs, while having lower takeoff and landing energy consumption and thrust requirements. This research proposes a high-peak-power distributed electric propulsion (DEP) system model and overload design method for eSTOL UAVs to further improve the power and thrust of the propulsion system. The model considers motor temperature factors with the throttle input, which is solved through three-round iterative calculations. The experimental and simulation results indicate that the maximum error of the high-peak-power propulsion unit model without considering temperature is 19.52%, and the maximum error when considering temperature is 1.2%. The propulsion unit ground test indicates that the main factors affecting peak power are the duration of peak power and the temperature limit of the motor. Finally, the effectiveness of the propulsion system model is verified through ground tests and UAV flight tests.

An Aircraft-Manipulator System for Virtual Flight Testing of Longitudinal Flight Dynamics

A virtual flight test is the process of flying an aircraft model inside a wind tunnel in a manner that replicates free-flight. In this paper, a 3-DOF aircraft-manipulator system is proposed that can be used for longitudinal dynamics virtual flight tests. The system consists of a two rotational degrees-of-freedom manipulator arm with an aircraft wind tunnel model attached to the third joint. This aircraft-manipulator system is constrained to operate for only the longitudinal motion of the aircraft. Thus, the manipulator controls the surge and heave of the aircraft whilst the pitch is free to rotate and can be actively controlled by means of an all-moving tailplane of the aircraft if required. In this initial study, a flight dynamics model of the aircraft is used to obtain dynamic response trajectories of the aircraft in free-flight. A model of the coupled aircraft-manipulator system developed using the Euler method is presented, and PID controllers are used to control the manipulator so that the aircraft follows the free-flight trajectory (with respect to the air). The inverse kinematics are used to produce the reference joint angles for the manipulator. The system is simulated in MATLAB/Simulink and a virtual flight test trajectory is compared with a free-flight test trajectory, demonstrating the potential of the proposed system for virtual flight tests.

Rapid Integrated Design Verification of Vertical Take-Off and Landing UAVs Based on Modified Model-Based Systems Engineering

Unmanned Aerial Vehicle (UAV) development has garnered significant attention, yet one of the major challenges in the field is how to rapidly iterate the overall design scheme of UAVs to meet actual needs, thereby shortening development cycles and reducing costs. This study integrates a “Decision Support System” and “Live Virtual Construct (LVC) environment” into the existing Model-Based Systems Engineering framework, proposing a Modified Model-Based Systems Engineering methodology for the full-process development of UAVs. By constructing a decision support system and a hybrid reality space—which includes pure digital modeling and simulation analysis software, semi-physical simulation platforms, real flight environments, and virtual UAVs—we demonstrate this method through the development of the electric vertical take-off and landing fixed-wing UAV DB1. This method allows for rapid, on-demand iteration in a fully digital environment, with feasibility validated by comparing actual flight test results with mission indicators. The study results show that this approach significantly accelerates UAV development while reducing costs, achieving rapid development from “demand side to design side” under the “0 loss” background. The DB1 platform can carry a 2.5 kg payload, achieve over 40 min of flight time, and cover a range of more than 70 km. This work provides valuable references for UAV enterprises aiming to reduce costs and increase efficiency in the rapid commercialization of UAV applications.

Enhancing Aircraft Glide Performance through Wing Geometry Modifications

Modifications to wing geometry can significantly influence the glide performance of an aircraft, affecting critical aspects such as lift, drag, and overall flight efficiency. This study investigates how variations in wing design parameters, including aspect ratio, wing loading, and camber, impact the glide ratio and performance of fixed-wing aircraft. Using a combination of computational fluid dynamics (CFD) simulations and scaled model flight tests, the research provides a detailed analysis of how these geometric adjustments affect aerodynamic characteristics during unpowered flight. The results indicate that increasing the aspect ratio, which involves lengthening the wingspan relative to the wing chord, significantly improves glide performance by reducing induced drag, thus enhancing the aircraft's lift-to-drag ratio. This improvement is particularly beneficial during extended glide phases, as it allows for greater distances covered per unit of altitude loss. Adjustments to wing loading, defined as the aircraft’s weight divided by the wing area, showed that lower wing loading generally improves glide efficiency but at the cost of increased sensitivity to turbulence and gusts. Changes in camber, or the curvature of the wing, had more complex effects; higher camber increased lift but also raised drag, highlighting the need for a balanced approach depending on flight conditions.

Research on Minimum Unstick Speed Flight Test Method for Civil Aircraft

The minimum unstick speed (VMU) is defined as the calibrated airspeed at which an aircraft can safely lift off and continue its takeoff without any difficulties. The VMU flight test, characterized by low-speed and high angle of attack under the influence of ground effect, poses significant challenges and high risks, making it one of the most hazardous flight test subjects in civil aircraft flight test. The research on VMU flight test methods for civil aircraft is of utmost importance in strengthening the foundation of flight test technology, improving flight test efficiency, and ensuring flight test safety.

Research on Airworthiness Requirements for Function and Reliability Flight Test of Civil Aircraft

Function and reliability flight testing is an important trial for civil aircraft airworthiness certification, and is a part of the qualified acceptance flight tests that confirm that the aircraft, components, and equipment are reliable and functioning properly. This article studies the airworthiness requirements for function and reliability flight testing in CCAR21 and Appendix B of AC25-7D, and combines practical experience with civil aircraft models to analyze the requirements for flight testing time, configurations, procedures, and problem requirements, and provide recommendations for civil aircraft function and reliability flight testing.