Modern low-altitude unmanned aircraft (UA) detection and surveillance systems mostly adopt the multi-sensor fusion technology scheme of radar, visible light, infrared, acoustic and radio detection. Firstly, this paper summarises the latest research progress of UA and bird target detection and recognition technology based on radar, and provides an effective way of detection and recognition from the aspects of echo modeling and micro motion characteristic cognition, manoeuver feature enhancement and extraction, motion trajectory difference, deep learning intelligent classification, etc. Furthermore, this paper also analyses the target feature extraction and recognition algorithms represented by deep learning for other kinds of sensor data. Finally, after a comparison of the detection ability of various detection technologies, a technical scheme for low-altitude UA surveillance system based on four types of sensors is proposed, with a detailed description of its main performance indicators.

This work investigates the role of flexibility and resonant excitation on the deformation mechanism and aerodynamic performance of flapping wings. A hummingbird-inspired wing (HIW) is considered and designed to have a bone-like stiffener made of carbon fibre/epoxy (CF/E) composite attached to a membrane made of carbon nanotubes/polypropylene (CNTs/PP) nanocomposite representing the flexible part of the natural wing. The designed HIW model is analysed through fluid-structure interaction simulations performed at frequencies near and at resonant frequency. It is found that HIW generates desired bending and twisting deformations that are coupled. These deformation mechanisms are studied in detail with the help of time-varying deflections and bending-twisting angles. Further, the simultaneous effect of these parameters on the aerodynamic performance of the wing is also investigated. It is observed that the coupled nature of bending and twisting deformations is critical in enhancing the aerodynamic performance of flapping wings. In addition to that, the resonance generates higher amplitude of desired structural deformations that further enhances thrust as well as lift generation capability of the wing. The underlying mechanism for this is also explained by studying the flow around the deflected surface of the wing. Compared to off-resonant frequencies, vorticity and pressures are substantially higher for the wing at resonance. A physical model of HIW is realised using CNTs/PP and CF/E composites to perform experimental wing motion analysis and to validate the computational results. In conclusion, the present study provides a basis to design efficient biomimetic flapping wings for micro aerial vehicles (MAVs) by exploring flexibility and resonant excitation.

Replacing kerosene with hydrogen as a fuel for propelling aeroplanes will undoubtably have ramifications for the existing certification basis and the necessary means of compliance. What this paper attempts to do is explain how a future hydrogen-powered aeroplane could be certified and how this will influence the aircraft’s design. Emphasis has been placed on the safety of hydrogen with regards flammability, ignition energy, cryogenic states and crashworthiness. The influence of certification on a future hydrogen-fuelled aeroplane’s configuration has been established. Lessons learnt from rockets are limited in scope. Consideration of hydrogen’s cryogenic and ambient temperature properties has established some fundamental safety principles. Fuel system crashworthiness influence on certification has been examined. An explosion prevention certification scheme has been developed. It is proposed to exclude oxygen from the fuel system and avoid accumulation of leaked or permeated hydrogen from adjacent zones. Three generic hydrogen-fuelled configurations have been considered for certification: adapting conventional airliner design, hydrogen-electric (fuel cell) propulsion and an unconventional approach. Hydrogen as a safe gas turbine fuel has been examined in technical and environmental terms. Further experimental work to close knowledge gaps in the aviation use of hydrogen has been suggested. In conclusion the necessary changes to the certification basis are outlined. Comments as to what the configuration of a future hydrogen-fuelled aeroplane might look like are provided. These observations are based on analysis of hydrogen’s properties, the existing certification basis, knowledge gaps, and what Special Conditions and Acceptable Means of Compliance might emerge in a future design Type Certification.

Although the problem of locked-in deep stall is well documented over many years, there currently exists no consistent procedure that can guarantee recovery. Past studies have suggested that it might be possible to rock the aircraft in pitch to destabilise the statically stable deep stall trim point, thereby gaining enough momentum to push the nose down. However, the methods used in these studies are either of preliminary or empirical nature and cannot guarantee recovery. In this paper, we use bifurcation analysis to derive a recovery manoeuvre, specifically by assessing the aircraft’s nonlinear frequency response under an elevator forcing. The ensuing nonlinear Bode plot detects unstable (divergent) solutions near resonance that contribute to a successful deep stall recovery. Moreover, the nonlinear resonant frequency is slightly lower than the result obtained using linear analysis, and time simulation shows that relying on the linear result does not lead to a successful recovery. It is also found that at the high angles of attack associated with deep stall, the frequency separation between the short period and phugoid mode is significantly reduced, leading to only one visible peak in the frequency response. This feature is also reflected in the time-domain step response.

The aerodynamic modelling is one of the challenging tasks that is generally established using the results of the computational fluid dynamic software and wind tunnel analysis performed either on the scaled model or the prototype. In order to improve the confidence of the estimates, the conventional parameter estimation methods such as equation error method (EEM) and output error method (OEM) are more often applied to extract the aircraft’s stability and control derivatives from its respective flight test data. The quality of the estimates gets influenced due to the presence of the measurement and process noises in the flight test data. With the advancement in the machine learning algorithms, the data driven methods have got more attention in the modelling of a system based on the input-output measurements and also, in the identification of the system/model parameters. The research article investigates the longitudinal stability and control derivatives of the aerodynamic models by using an integrated optimisation algorithm based on a recurrent neural network. The flight test data of Hansa-3 and HFB 320 aircraft were used as case studies to see the efficacy of the parameter estimation algorithm and further, the confidence of the estimates were demonstrated in terms of the standard deviations. Finally, the simulated variables obtained using the estimates demonstrate a qualitative estimation in the presence of the noise.

In the preliminary design phase of aircraft design, estimating the production cost accurately is a challenging task. At this stage, many design parameters that affect the overall cost are still undefined. This paper establishes cost-estimation models for civil, commercial aircraft using a parametric cost analysis (PCA) approach. Aircraft are characterised based on their size, ranging from a wide body to executive jets, into four categories. Key design parameters, such as maximum take-off weight, number of passengers, range, wing area, span, fuselage length, to name a few, are likely to be available in the preliminary design stage and significantly impact the aircraft design. These variables either directly or indirectly affect the overall production cost or performance. The PCA approach includes both correlation and multiple linear regression techniques. The empirical models thus developed were able to predict the aircraft cost with an error of less than ±4% for all aircraft categories considered. Two aircraft in each defined category were not part of the PCA models and were used to verify the models. The proposed models provide the ability to estimate the aircraft cost quickly in the early stages of the preliminary design phase and provide the possibility of performing parametric studies involving the key variables to determine the cost sensitivity to the main design parameters.

The unmanned aerial vehicle (UAV) flocking among obstacles was transferred to a velocity-controllable UAV flocking problem, which means that multi-UAV gradually form and maintain the $\alpha$ -lattice geometry as they track the desired flocking velocity, and can be applied to tasks such as obstacle avoidance and velocity tracking. Velocity-controllable UAV flocking problem is a multi-objective flocking controller parameters optimisation problem, for which we design flocking velocity and geometry objective function, and solve them using a multi-objective particle swarm optimisation algorithm (MOPSO). On this basis, to address the problem that MOPSO has random results and long computation time, we propose to use a neural network (NN) to approximate the mathematical relationship between the UAV flocking state and the flocking controller parameters. We simulate the flight process of 5 and 49 UAVs performing obstacle avoidance and velocity tracking tasks, respectively. The results show that the proposed UAV flocking controller has better convergence performance, obtains reproducible results, reduces computation time, and can be used for large-scale UAV flocking control.

This paper presents a relative fuel burn evaluation of the transonic strut-braced-wing configuration for the regional aircraft class in comparison to an equivalent conventional tube-and-wing aircraft. This is accomplished through multipoint aerodynamic shape optimisation based on the Reynolds-averaged Navier-Stokes equations. Aircraft concepts are first developed through low-order multidisciplinary design optimisation based on the design missions and top-level aircraft requirements of the Embraer E190-E2. High-fidelity aerodynamic shape shape optimisation is then applied to wing–body–tail models of each aircraft, with the objective of minimising the weighted-average cruise drag over a five-point operating envelope that includes the nominal design point, design points at $\pm 10\%$ nominal $C_L$ at Mach 0.78, and two high-speed cruise points at Mach 0.81. Design variables include angle-of-attack, wing (and strut) twist and section shape degrees of freedom, and horizontal tail incidence, while nonlinear constraints include constant lift, zero pitching moment, minimum wing and strut volume, and minimum maximum thickness-to-chord ratios. Results show that the multipoint optimised strut-braced wing maintains similar features to those of the single-point optimum, and compromises on-design performance by only two drag counts to achieve up to 11.6% reductions in drag at the off-design conditions. Introducing low-order estimates for approximating full aircraft performance, results indicate that the multipoint optimised strut-braced-wing regional jet offers a 13.1% improvement in cruise lift-to-drag ratio and a 7.8% reduction in block fuel over a 500nmi nominal mission when compared to the similarly optimised Embraer E190-E2-like conventional tube-and-wing aircraft.