Adjacent Flight Research Articles

On novel distributed fixed-time formation tracking of multiple hypersonic flight vehicles with collision avoidance

This paper aims to achieve collision-free formation tracking for multiple hypersonic flight vehicles without introducing conventional approximators such as fuzzy logic systems and neural networks. By relying on the hierarchical control theory, a globally fixed-time distributed formation control protocol with guaranteed tracking behaviors is proposed. Firstly, for the purpose of deriving the virtual control commands in the three-dimensional translational dynamics, a fixed-time consensus control input is presented. Then, by designing a comprehensive performance-preserving feedback control law, the actual control commands are derived, so that the virtual control inputs can be tracked timely and accurately. Meanwhile, with resort to a novel exponential-type artificial potential function, a collision-free control input is proposed to avoid close proximity between adjacent hypersonic flight vehicles. Summarily, the outstanding advantage of the proposed protocol is that it simultaneously realize the collision-free formation tracking, fixed-time stability and performance-preserving control for multiple hypersonic flight vehicles with uncertain dynamics. Lyapunov stability criterion verifies the closed-loop stability, showing that the error signals can attenuate to a tiny region around the origin within a user-specified time. Finally, comparative numerical simulations are performed to further demonstrate the theoretical results.

Wireless Network-Aided Delay Information System Correlation with Airport Grid Distribution Based on Multideterminants Big Data

The intelligent sensing and communication technology in the airports’ grid information system provides a multidimensional big data set for analyzing flight delays. These data from air traffic control, weather, and multiple determinants will cause initial flight delays. Due to the influence of adjacent flight time correlation, the initial delay causes the delay of subsequent flights, discovered by mining information sensing data, forming the phenomenon of flight delay diffusion. Different determinants will lead to the delay diffusion form of different regions, and more seriously, it will lead to “disaster area” delay in the whole regional grid information structure. To analyze the spatial impact of each factor on flight delay and explore the regional distribution of delay determinants, this paper combined the spatial regression model and determined the key explanatory variables by statistical and processing of the aviation system data. The case study showed the spatial airport delay characteristics in terms of aircraft movements in China. After processing intelligent sensing and communication data, the results show that there is a spatial effect between airports in terms of delay and determinants. The high-delay clusters of delay constraints principally occurred in the Beijing-Tianjin-Hebe and Yangtze River Delta urban agglomerations. Direct flights, weather, new flight routes, take-off, and landing capacity have a more critical impact on spatial airport delays. The use of Internet of Things technology to perceive, analyze, and integrate multiple information of airport delay and combine spatial analysis models can accurately mine delay characteristics and effectively achieve digital and intelligent flight delay management.

Effect of scan angle on ALS metrics and area-based predictions of forest attributes for balsam fir dominated stands

Abstract In this study, we assessed the effect of airborne laser scanning (ALS) scan angle on point cloud metrics and the estimation of forest attributes in balsam fir (Abies balsamea (L.) Mill.) dominated forests of western Newfoundland, Canada. We collected calibration data from ground plot locations representing varying scan angles from two flight lines: within 4° of nadir in one flight line, and either 11–20° from nadir (low scan angle plots: L), or 21–30° from nadir (high scan angle plots: H) in an adjacent flight line. We computed three sets of ALS point cloud metrics for each ground plot using ALS data from: individual flight lines (near-nadir and off-nadir) and data from all available flight lines (up to 4) combined (aggregated, as commonly used in an operational inventory context). We generated three sets of models for each of the L and H plots using the ALS metric sets, and applied the models to independent validation data. We analysed the effect of scan angle on both the ALS metrics and performance statistics for area-based models generated using the L and H datasets. Our results demonstrate that off-nadir scan angles significantly affected (P < 0.05) specific metrics from both L (i.e. coefficient of variation (COVAR)) and H (i.e. maximum height, 95th percentile of height, mean height) plots, although the effects were trivial (mean absolute differences were ≤ 0.01 for COVAR and < 0.3 m for the height metrics). Forest attribute predictions using these and other metrics were also significantly affected (P < 0.05), namely gross merchantable volume (GMV), total volume (TVOL) and aboveground tree biomass (AGB) from L; and Lorey’s mean height (HGT), mean diameter at breast height (DBH), and GMV from H. We further demonstrated that combining ALS data from all available flight lines significantly increased errors for the predictions of HGT, GMV, and TVOL using L, and significantly reduced errors of HGT using H when compared to errors resulting from models developed with near-nadir data. While the differences in prediction errors were significant, they were small, with differences in mean absolute prediction errors all <1.3 per cent. Based on our results, we concluded that the effects of large scan angles, up to 30° off-nadir, on area-based forest attribute predictions were minimal in this study, which used ALS metrics calculated from ALS returns with a height above ground >2 m for balsam fir-dominated forests. This result may provide for operational efficiencies in implementing enhanced forest inventories in this particular forest environment.

SGDAN-A Spatio-Temporal Graph Dual-Attention Neural Network for Quantified Flight Delay Prediction.

There has been a lot of research on flight delays. But it is more useful and difficult to estimate the departure delay time especially three hours before the scheduled time of departure, from which passengers can reasonably plan their travel time and the airline and airport staff can schedule flights more reasonably. In this paper, we develop a Spatio-temporal Graph Dual-Attention Neural Network (SGDAN) to learn the departure delay time for each flight with real-time conditions at three hours before the scheduled time of departure. Specifically, it first models the air traffic network as graph sequences, what is, using a heterogeneous graph to model a flight and its adjacent flights with the same departure or arrival airport in a special time interval, and using a sequence to model the flight and its previous flights that share the same aircraft. The main contributions of this paper are using heterogeneous graph-level attention to learn the influence between the flight and its adjacent flight together with sequence-level attention to learn the influence between the flight and its previous flight in the flight sequence. With aggregating features from the learned influence from both graph-level and sequence-level attention, SGDAN can generate node embedding to estimate the departure delay time. Experiments on a real-world large-scale data set show that SGDAN produces better results than state-of-the-art models in the accurate flight delay time estimation task.

Removing Stripe Noise Based on Improved Statistics for Hyperspectral Images

Stripe noise still affects full-spectrum airborne hyperspectral imager (FAHI) images after laboratory radiometric calibration, which seriously affects the subsequent applications of the imager. Therefore, two state-of-the-art methods, median linear correction (MLC) and Fourier transform filtering (FTF), were proposed to restore FAHI images, and the residual stripes were removed in most cases. However, these methods have their own limitations. For instance, the restored image has a slight “shadow” in cases where the high-response digital numbers (DNs) of the detector are aligned with the flight direction. This letter proposes a new method based on improved statistics to restore FAHI images. In this method, the hyperspectral image data from the adjacent flight paths is used to obtain the uniform response DNs for nearly identical low and high irradiances. Subsequently, a statistics-based MLC method is used to eliminate the stripe noise. To quantitatively evaluate the restoration results, we compared results with MLC and FTF methods. The change in mean value and mean relative deviation of the proposed method for the high-response DNs area of the image is 0.25% and 0.97%, respectively, better than that of the other two methods. The experimental results demonstrate that the proposed method is effective for removing stripe noise and preserving accurate image information of push-broom hyperspectral imagery.

Lightweight Integrated Solution for a UAV-Borne Hyperspectral Imaging System

The rapid development of unmanned aerial vehicles (UAVs), miniature hyperspectral imagers, and relevant instruments has facilitated the transition of UAV-borne hyperspectral imaging systems from concept to reality. Given the merits and demerits of existing similar UAV hyperspectral systems, we presented a lightweight, integrated solution for hyperspectral imaging systems including a data acquisition and processing unit. A pushbroom hyperspectral imager was selected owing to its superior radiometric performance. The imager was combined with a stabilizing gimbal and global-positioning system combined with an inertial measurement unit (GPS/IMU) system to form the image acquisition system. The postprocessing software included the radiance transform, surface reflectance computation, geometric referencing, and mosaic functions. The geometric distortion of the image was further significantly decreased by a postgeometric referencing software unit; this used an improved method suitable for UAV pushbroom images and showed more robust performance when compared with current methods. Two typical experiments, one of which included the case in which the stabilizing gimbal failed to function, demonstrated the stable performance of the acquisition system and data processing system. The result shows that the relative georectification accuracy of images between the adjacent flight lines was on the order of 0.7–1.5 m and 2.7–13.1 m for cases with spatial resolutions of 5.5 cm and 32.4 cm, respectively.

An integrated optimization mode for multi-type aircraft flight scheduling and routing problem.

This paper proposes an optimization model for the integrated aircraft flight scheduling and routing problem, which allows a simultaneous determination of the departure time of each flight trip and assignment of a set of aircraft located at different airports to perform all flight trips. The proposed model envisages that each flight trip is covered by its own particular aircraft type or a larger airplane. Further, departure and arrival times of each flight trip are within a flexible time window in its aircraft's route and origin/destination airports, and the number of airplanes firstly distributed in the base airports is fully accounted for in the model. The model not only can effectively minimize weighted operation costs for the number of airplanes and the total idle time for adjacent flight trips covered by an aircraft, but also can maximize the number of transported passengers. This paper further presents a two-stage heuristic approach based on the ant colony optimization algorithm, which efficiently finds the most acceptable solutions. The above algorithm is used to generate a series of aircraft routes, and a polynomial algorithm is designed to obtain their feasible flight trip timetable. Finally, the model is applied to a case study to design the integrated aircraft flight scheduling and routing plan for a real airline in China. A comparative analysis of the conventional and proposed models proved the latter's feasibility.

Retrieving Directional Gap Fraction, Extinction Coefficient, and Effective Leaf Area Index by Incorporating Scan Angle Information From Discrete Aerial Lidar Data

The scan angle information implicitly contained within the 3-D point cloud data (PCD) generated from light detection and ranging strongly affects the retrieval accuracy of the forest canopy structural parameters. Using information generated from overlapping aerial laser scanning (ALS) flight paths with multiple scan angles over a forest canopy can help to remove the occlusion effects between foliage elements, ultimately creating a relative comprehensive PCD. In this paper, we develop a novel physically based scan angle correction algorithm to retrieve the effective leaf area index (LAIe) of a forest canopy using ALS. Furthermore, we investigate the effects of scan angle and the number of ALS overpass lines from adjacent flight paths over a forest canopy on directional gap fraction (DGF) estimates. Our results suggest that ALS-based LAIe estimates capture 71.35% of the variations in LAIe derived from digital hemispherical photography. A forest canopy point cloud created using PCD from multiple overlapping ALS flight paths was sufficient to quantitatively reveal the anisotropy characteristics of DGF variations. These results suggest that scan angle information should not be neglected in retrieving forest canopy structural parameters, especially when using ALS data collected with a wide scan angle (i.e., −30° to 30° in this paper). Finally, this paper provides a solid foundation to characterize the 3-D spatial distribution of a forest radiation regime using ALS-based forest PCD.

Feather corticosterone content in predatory birds in relation to body condition and hepatic metal concentration

This study investigated the feasibility of measuring corticosterone in feathers from cryo-archived raptor specimens, in order to provide a retrospective assessment of the activity of the stress axis in relation to contaminant burden. Feather samples were taken from sparrowhawk Accipiter nisus, kestrel Falco tinnunculus, buzzard Buteo buteo, barn owl Tyto alba, and tawny owl Strix aluco and the variation in feather CORT concentrations with respect to species, age, sex, feather position, and body condition was assessed. In sparrowhawks only, variation in feather CORT content was compared with hepatic metal concentrations. For individuals, CORT concentration (pgmm−1) in adjacent primary flight feathers (P5 and P6), and left and right wing primaries (P5), was statistically indistinguishable. The lowest concentrations of CORT were found in sparrowhawk feathers and CORT concentrations did not vary systematically with age or sex for any species. Significant relationships between feather CORT content and condition were observed in only tawny owl and kestrel. In sparrowhawks, feather CORT concentration was found to be positively related to the hepatic concentrations of five metals (Cd, Mn, Co, Cu, Mo) and the metalloid As. There was also a negative relationship between measures of condition and total hepatic metal concentration in males. The results suggest that some factors affecting CORT uptake by feathers remain to be resolved but feather CORT content from archived specimens has the potential to provide a simple effects biomarker for exposure to environmental contaminants.

A scan‐angle correction for thermal infrared multispectral data using side lapping images

Thermal infrared multispectral scanner (TIMS) images, acquired with side lapping flight lines, provide dual angle observations of the same area on the ground and can thus be used to estimate variations in the atmospheric transmission with scan angle. The method was tested using TIMS aircraft data for six flight lines with about 30% sidelap for an area within Joshua Tree National Park, California. Generally the results correspond to predictions for the transmission scan‐angle coefficient based on a standard atmospheric model although some differences were observed at the longer wavelength channels. A change was detected for the last pair of lines that may indicate either spatial or temporal atmospheric variation. The results demonstrate that the method provides information for correcting regional survey data (requiring multiple adjacent flight lines) that can be important in detecting subtle changes in lithology.

A New Concept for Vertical Separation

The ICA system which is now being considered by the Civil Aviation Administrations in the UK and the USA is based on a new height unit, the ‘millica’. Below an arbitrary fixed level (29000 ft) this unit is equal to 0.3 m; above that level it increases gradually, the rate of increase corresponding to the standard deviation of aircraft height from assigned cruising level. At 10 000 m the unit is equal to 0.325 m and 15 000 m to 0.477 m. In this way the ratio between the separation of cruising levels and the standard deviation of the departure from assigned level remains constant; that is to say, the safety margin is constant. At present, cruising levels up to 29 000 ft are separated by 1000 ft and above this level by 2000 ft, so that there are five cruising levels between 29000 and 39000 ft; in the new system there would be nine.If δh is the height difference, δp the barometric pressure difference and p the mean atmospheric density in this interval, it is clear that δp = pδh and δh(1/p)δp. From this it follows that if δh is constant between adjacent flight levels the δp decreases with altitude and the vertical separation safety factor also decreases.If, as has sometimes been suggested, δp remains constant between adjacent flight levels, then δh will increase with altitude and the safety factor will increase also.