A Flight Trajectory Prediction Method Based on Internal Relationships between Attributes

The rapid development of the aviation industry urgently requires airspace traffic management,and flight trajectory prediction is a core component of airspace traffic management.Flight trajectory is a multidimensional time series with rich spatio-temporal characteristics,and existing flight trajectory prediction methods only target the trajectory point temporal relationships,but not the implicit interrelationships among the trajectory point attributes.In this paper,a graph convolutional network(AR-GCN)based on the intra-attribute relationships is proposed for solving the flight track prediction problem.First,the network extracts the temporal features of each attribute and fuses them with the original features of the attribute to obtain the enhanced attribute features,then extracts the implicit relationships between attributes as inter-attribute relationship features.Secondly,the enhanced attribute features are used as nodes and the inter-attribute relationship features are used as edges to construct the inter-attribute relationship graph.Finally,the graph convolutional network is used to aggregate the attribute features.Based on the full fusion of the above features,we achieved high accuracy prediction of the trajectory.In this paper,experiments are conducted on ADS-B historical track data.We compare our method with the classical method and the proposed method.Experimental results show that our method achieves significant improvement in prediction accuracy.

A survey of numerical algorithms for trajectory optimization of flight vehicles

As one of the important components of computational flight mechanics and control,numerical algorithms of trajectory optimization for flight vehicles are currently studied by many researchers in aerospace engineering to completely solve these difficult problems,but few papers on the survey of this research field have been published recently.Based on the investigation of more than one hundred literatures,considering the application perspectives of computational flight mechanics and recent developments of trajectory optimization,the numerical algorithms of trajectory optimizations for aerospace vehicles are summarized and systematically analyzed.This paper summarized the basic principle,characteristics and application for all kinds of current trajectory optimization algorithms;and introduced some new methods and theories appearing in recent years.Finally,collaborative trajectory optimization for many flight vehicles,and hypersonic vehicle trajectory optimization were mainly reviewed in this paper.In the conclusion of this paper,the future research properties are presented regarding to numerical algorithms of trajectory optimization and control for flight vehicles as follows:collaboration and antagonization for many flight vehicles and multiple targets,global,real-time online,high accuracy of 7-D trajectory,considering all kinds of unknown random disturbances in trajectory optimization,and so on.

Research on Designing Profiled Rod Warhead

A new Kinetic Energy Rod( KER) warhead named profiled rod warhead is proposed in this paper.Based on the design of profiled rod warhead,a model of profiled rod driven by detonation is established. The detonation process is simulated by ANSYS / LS-DYNA,and the deployment velocity and initial flight attitude of rod are achieved. In addition,static rod deployment testing are performed to investigate the damage effect,the spatial flight attitude and deployment velocity. A satisfactory agreement is obtained by the comparison between numerical results and testing results. Meanwhile,the profiled rod studies are conducted to determine a higher penetrability compared with traditional cylindrical rods. Rigid body dynamics equations of profiled rod,which accounts for the influence of air resistance,are set up to predict the flight trajectory of long-distance. The results show that the profiled rod may provide a better penetration angle which still maintains a significant penetrability against projectiles when the rods move off long-distance range.

Adaptive temporal patterns of echolocation and flight behaviors used to fly through varied-sized windows by 2 species of high duty cycle bats

As actively sensing animals guided by acoustic information, echolocating bats must adapt their vocal–motor behavior to various environmentsand behavioral tasks. Here, we investigated how the temporal patterns of echolocation and flight behavior were adjusted in 2 species of batswith a high duty cycle (HDC) call structure, Rhinolophus ferrumequinum and Hipposideros armiger, when they flew along a straight corridorand then passed through windows of 3 different sizes. We also tested whether divergence existed in the adaptations of the 2 species. Both H.armiger and R. ferrumequinum increased their call rates by shortening the pulse duration and inter-pulse interval for more rapid spatial samplingof the environment when flying through smaller windows. Bats produced more sonar sound groups (SSGs) while maintaining a stable proportion of calls that made up SSGs during approaches to smaller windows. The 2 species showed divergent adjustment in flight behavior across3 different window sizes. Hipposideros armiger reduced its flight speed to pass through smaller windows while R. ferrumequinum increasedits flight speed. Our results suggest that these 2 species of HDC bats adopt similar acoustic timing patterns for different tasks although theyperformed different flight behaviors.

New reference trajectory optimization algorithm for a flight management system inspired in beam search

With the objective of reducing the flight cost and the amount of polluting emissions released in the atmosphere, a new optimization algorithm considering the climb, cruise and descent phases is presented for the reference vertical flight trajectory. The selection of the reference vertical navigation speeds and altitudes was solved as a discrete combinatory problem by means of a graphtree passing through nodes using the beam search optimization technique. To achieve a compromise between the execution time and the algorithm＇s ability to find the global optimal solution, a heuristic methodology introducing a parameter called ‘‘optimism coefficient was used in order to estimate the trajectory＇s flight cost at every node. The optimal trajectory cost obtained with the developed algorithm was compared with the cost of the optimal trajectory provided by a commercial flight management system（FMS）. The global optimal solution was validated against an exhaustive search algorithm（ESA）, other than the proposed algorithm. The developed algorithm takes into account weather effects, step climbs during cruise and air traffic management constraints such as constant altitude segments, constant cruise Mach, and a pre-defined reference lateral navigation route. The aircraft fuel burn was computed using a numerical performance model which was created and validated using flight test experimental data.