High-altitude Flight Research Articles

Viscosity and Density of Narrow Distillation Cuts from Refined Petroleum- and Synthetic-Derived Distillates in the -60 to +60 °C Range.

Aviation turbine fuel (jet fuel) must remain fluid enough for use at low temperatures typically experienced during high-altitude flights. The viscosity-temperature relationship of petroleum-derived jet fuel is described by the MacCoull correlation in ASTM D341. The maximum kinematic viscosity of jet fuel at -20 °C is regulated by specification, but for long-distance flights, viscosity of <12 mm2 s-1 at -40 °C is important. For synthesized paraffinic kerosene (SPK) to be approved as a synthetic jet fuel, compliance with these viscosity limits is imperative. A petroleum-based kerosene and SPK from wax hydrocracking were distilled into narrow cut (5 °C range) fractions, and for each narrow cut, density, viscosity, and refractive index values were measured over the temperature range from +60 to -60 °C. The viscosity-temperature dependences of the petroleum-derived and synthetic narrow cuts were described with comparable accuracy (relative deviation <5%) by the MacCoull correlation. Calculation of kinematic viscosity at -40 °C by extrapolating data measured at ≥-20 °C underpredicted viscosity for >200 °C boiling kerosene cuts, with a maximum relative deviation of 6.6%. The freezing point is another jet fuel property that is regulated by specification. Good agreement (±1.3 °C) was found between the end of the melting endotherm obtained by differential scanning calorimetry (DSC) and the freezing point determined according to ASTM D2386. Local maxima/minima in the freezing point of distillation cuts with increasing boiling point were observed and could be related to the freezing point characteristics of the n-alkanes.

The Application of Fuel Cell and Battery Technologies in Unmanned Aerial Vehicles (UAVs): A Dynamic Study

The harmful influences of the fossil fuels on the environments have convinced the authorities to set official targets to 100% phase out the sales or registrations of new internal combustion engines (ICEs). As alternatives, batteries and fuel cells are suggested to provide the required power for different applications such as cars, buses, trucks, etc. Although there have been many investigations on the possibility of using integrated fuel cell and battery system as the prime mover for different types of vehicles, limited number of investigations have been developed in the airplane sector.At the current stage, the current suggested integrated system of battery and fuel cell is not able to provide the required power for huge passenger planes, but they can generate the needed electricity to run small size planes (around 100kW to 300 kW), hence the objective of the current study is related to the domain of Unmanned Aerial Vehicles (UAVs). UAVs are designed to fulfill long and high-altitude flight missions. The flight duration and flight altitude have been proved to be improved using the proton exchange membrane fuel cells (PEMFCs) as the prime-mover of the UAVs. However, the low acceleration of the PEMFCs has triggered the idea of combining PEMFCs and Lithium-Ion (Li-ion) battery. Thus, the integrated system can improve the low range of batteries by maintaining high acceleration and fast re-fueling time.Among different types of fuel cells, PEMFCs are established to be the best option for mobility applications, and the well-known Nickel Manganese Cobalt (NMC), and Lithium Titanite Oxide (LTO) Li-Ion batteries are considered as the most efficient types. Among the existing Li-Ion batteries in the market, LTO enjoys from the highest performance, lifespan, and safety by higher costs, whereas NMC provides acceptable performance with low costs and high specific energy. In comparison to the batteries, proton exchange membrane fuel cells (PEMFCs) have faster refueling time and higher ranges, hence the integration of batteries and fuel cells can provide the needs of UAVs.The utilization of PEMFC in an UAV results in the size and weight reduction of the system in addition to improving the flight endurance. Batteries can also ameliorate the acceleration and thrust of the system. So far, it is believed that fuel cells can be suitable for cruise flight while batteries are more appropriate for other flight modes. This study analyzes the possibility of integrating the PEMFC technology to the batteries as an alternative for fossil fuel-based combustion engines for the small sized UAV application. The proposed hybrid system, which is shown in Fig. 1., is designed to provide around 950W power for a UAV with a weight of 14 kg. PEMFC will be used as the selected type of fuel cell while NMC is the considered type of Li-Ion battery. The goal of this study is the characterize the dynamic performance of the current integrated system in an optimized condition. The integrated model of the fuel cell and battery is developed in the MATLAB/Simulink software to be controlled by an energy management system, which provides power to a DC variable power load, representing the different loads of an UAV flight. The load is mainly supplied by the fuel cell, while the battery intervenes in the following cases: As a support when the load is too high for the fuel cell,As a support when the fuel cell takes too long to respond to a load variation,As an additional load when the state of the charge of the battery is low (meaning that the fuel cell recharges the battery). Figure 1

Preparing for space: Increasing technical readiness of low-cost high-performance remote sensing using high-altitude ballooning

Two widely available, small size, weight and power camera systems were flown above 97 % of Earth’s atmosphere and showed utility in single filter vegetation and soil analysis in a space analogue environment. The experiment was conducted as a low-cost verification and test analogue to flying on vastly more expensive low Earth orbit missions. Normalised Difference Vegetation Index (NDVI) was used as the metric by which performance was analysed for ground calibration testing, low and near-space altitude remote sensing. Ground calibration testing with a laboratory-grade spectrometer revealed that both cameras were able to return consistent NDVI results, and high-altitude balloon flight allowed similar data capture from an environment similar to space. Although compressed captured imagery had been processed using gamma correction and pre-image processing, these were able to be corrected provided that access to radiometrically-calibrated data was available. The two hobbyist cameras were shown to return scientifically useful results, demonstrating performance, and additionally their utility for citizen science applications in the near-space environment.

Preliminary Design and Analysis of Supersonic Business Jet Engines

Currently projected supersonic business jets target selected supersonic flight missions with Mach numbers of about 1.4 and a larger number of long-range subsonic flight missions. They form a new type of aircraft that is specially tailored to these requirements. The question arises as to which engine configurations and technology levels are required to support these new applications. This is addressed firstly by exploring the design space of potential working cycles. An aircraft model is used to translate the results of the cycle study into an expected aircraft range. An optimal core engine and fan configuration result from the cycle study and the derived mission ranges. The preliminary design of the low-pressure components is investigated in the second step based on the optimal core configuration. The highest non-dimensional parameters are encountered in subsonic flight conditions. The highest dimensional parameters are encountered in supersonic high-altitude flight conditions. High-overall-efficiency configurations do not result in optimal aircraft ranges. There is an optimal number of two fan stages and a specific thrust of about 300 m/s, resulting in a maximum aircraft range that is 11% superior to that achievable with a single-stage fan. A fan hub-to-tip ratio range that is comparable to that of military fans is desirable, with an aerodynamic lower limit around 0.37. The low-pressure turbine stage count is a compromise between turbine mass and size.

Comparison of building thermography approaches using terrestrial and aerial thermographic images

Thermography is commonly used for auditing buildings. Classical manual terrestrial thermography records images of individual buildings at a short distance. When auditing a large number of buildings (e.g. whole city districts) this approach reaches its limits. Using drones with thermographic cameras allows images to be recorded automatically from different angles, with faster speed and without violating property rights. However, an airborne camera has a significantly greater distance and more varied angles to a building compared to terrestrial thermography. To investigate the influence of these factors for building auditing, we perform a study evaluating seven different drone settings of varying flight speed, angle, and altitude. A comparison is drawn to manually recorded terrestrial thermographic images. While we find that a flight speed between 1m/s and 3m/s does not influence the thermographic quality, high flight altitudes and steep viewing angles lead to a significant reduction of visible details, contrast, and to falsified temperatures. A flight altitude of 12m over buildings is found to be the most suitable for the qualitative and quantitative analysis of rooftops and a qualitative analysis of façades. A flight altitude of 42m over buildings can only be used for qualitative audits with little detail.

Behavioral innovation and genomic novelty are associated with the exploitation of a challenging dietary opportunity by an avivorous bat

SummaryForaging on nocturnally migrating birds is one of the most challenging foraging tasks in the animal kingdom. Only three bat species (e.g., Ia io) known to date can prey on migratory birds. However, how these bats have exploited this challenging dietary niche remains unknown. Here, we demonstrate that I. io hunts at the altitude of migrating birds during the bird migration season. The foraging I. io exhibited high flight altitudes (up to 4945 m above sea level) and high flight speeds (up to 143.7 km h−1). I. io in flight can actively prey on birds in the night sky via echolocation cues. Genes associated with DNA damage repair, hypoxia adaptation, biting and mastication, and digestion and metabolism have evolved to adapt to this species’ avivorous habits. Our results suggest that the evolution of behavioral innovation and genomic novelty are associated with the exploitation of challenging dietary opportunities.

Dynamic Range of Luminance Perception in Acute Hypobaric Hypoxia.

Rizzi, Alessandro, Alice Plutino, Diego Vecchi, Anton Giulio Guadagno, and Marco Lucertini. Dynamic range of luminance perception in acute hypobaric hypoxia. High Alt Med Biol. 23:313-318, 2022.-The effects of acute hypobaric hypoxia, as potentially experienced in high altitude flight, on the detection of low contrast targets within a high dynamic range (DR) of luminance were investigated. The tests were performed after 10 minutes of adaptation to an ambient luminance level of 0.2 lx. Twenty-four individuals were exposed to hypobaric hypoxia at an altitude of 18,000 ft (5,490 m) inside a hypobaric chamber and were asked to identify the darkest one perceived from a grid of progressively less luminous patches. The results were compared with those obtained by the same subjects at sea level. The results indicate a global reduction of the DR perception during hypoxia, with a mean decrease of 0.023 cd/m2 (standard deviation ±0.064), which resulted statistically significant (p < 0.05). No significant correlations with oxygen saturation levels were observed. These findings might have practical applications in the design of cockpit's instruments, especially those dedicated to night-time flight missions at high altitudes.

Super-Resolution Images Methodology Applied to UAV Datasets to Road Pavement Monitoring

The increasingly widespread use of smartphones as real cameras on drones has allowed an ever-greater development of several algorithms to improve the image’s refinement. Although the latest generations of drone cameras let the user achieve high resolution images, the large number of pixels to be processed and the acquisitions from multiple lengths for stereo-view often fail to guarantee satisfactory results. In particular, high flight altitudes strongly impact the accuracy, and result in images which are undefined or blurry. This is not acceptable in the field of road pavement monitoring. In that case, the conventional algorithms used for the image resolution conversion, such as the bilinear interpolation algorithm, do not allow high frequency information to be retrieved from an undefined capture. This aspect is felt more strongly when using the recorded images to build a 3D scenario, since its geometric accuracy is greater when the resolution of the photos is higher. Super-Resolution algorithms (SRa) are utilized when registering multiple low-resolution images to interpolate sub-pixel information The aim of this work is to assess, at high flight altitudes, the geometric precision of a 3D model by using the the Morpho Super-Resolution™ algorithm for a road pavement distress monitoring case study.

Predicting the energy and exergy performance of F135 PW100 turbofan engine via deep learning approach

In the present study, the effects of flight-Mach number, flight altitude, fuel types, and intake air temperature on thrust specific fuel consumption, thrust, intake air mass flow rate, thermal and propulsive efficiecies, as well as the exergetic efficiency and the exergy destruction rate in F135 PW100 engine are investigated. Based on the results obtained in the first phase, to model the thermodynamic performance of the aforementioned engine cycle, Flight-Mach number and flight altitude are considered to be 2.5 and 30,000 m, respectively; due to the operational advantage of supersonic flying at high altitude flight conditions, and the higher thrust of hydrogen fuel. Accordingly, in the second phase, taking into account the mentioned flight conditions, an intelligent model has been obtained to predict output parameters (i.e., thrust, thrust specific fuel consumption, and overall exergetic efficiency) using the deep learning method. In the attained deep neural model, the pressure ratio of the high-pressure turbine, fan pressure ratio, turbine inlet temperature, intake air temperature, and bypass ratio are considered input parameters. The provided datasets are randomly divided into two sets: the first one contains 6079 samples for model training and the second set contains 1520 samples for testing. In particular, the Adam optimization algorithm, the cost function of the mean square error, and the active function of rectified linear unit are used to train the network. The results show that the error percentage of the deep neural model is equal to 5.02%, 1.43%, and 2.92% to predict thrust, thrust specific fuel consumption, and overall exergetic efficiency, respectively, which indicates the success of the attained model in estimating the output parameters of the present problem.

Extended Duration Orbiter Medical Project

Biomedical issues have presented a challenge to flight physicians, scientists, and engineers ever since the advent of high-speed, high-altitude airplane flight in the 1940s. In 1958, preparations began for the first manned space flights of Project Mercury. The medical data and flight experience gained through Mercury's six flights and the Gemini, Apollo, and Skylab projects, as well as subsequent space flights, comprised the knowledge base that was used to develop and implement the Extended Duration Orbiter Medical Project (EDOMP). The EDOMP yielded substantial amounts of data in six areas of space biomedical research. In addition, a significant amount of hardware was developed and tested under the EDOMP. This hardware was designed to improve data gathering capabilities and maintain crew physical fitness, while minimizing the overall impact to the microgravity environment. The biomedical findings as well as the hardware development results realized from the EDOMP have been important to the continuing success of extended Space Shuttle flights and have formed the basis for medical studies of crew members living for three to five months aboard the Russian space station, Mir. EDOMP data and hardware are also being used in preparation for the construction and habitation of International Space Station. All data sets were grouped to be non-attributable to individuals, and submitted to NASA s Life Sciences Data Archive.

Rush or relax: migration tactics of a nocturnal insectivore in response to ecological barriers

During their annual migration, avian migrants alternate stopover periods, for refuelling, with migratory flight bouts. We hypothesise that European Nightjars (Caprimulgus europaeus) adapt their daily migration tactics in association with biomes. We tracked the autumn migration of 24 European Nightjars, from breeding populations in Mongolia, Belgium and UK, using GPS-loggers and multi-sensor data loggers. We quantified crepuscular and nocturnal migration and foraging probabilities, as well as daily travel speed and flight altitude during active migration in response to biomes. Nightjars adopt a rush tactic, reflected in high daily travel speed, flight altitude and high migration probabilities at dusk and at night, when travelling through ecological barriers. Migration is slower in semi-open, hospitable biomes. This is reflected in high foraging probabilities at dusk, lower daily travel speed and lower migration probabilities at dusk. Our study shows how nightjars switch migration tactics during autumn migration, and suggest nightjars alternate between feeding and short migratory flight bouts within the same night when travelling through suitable habitats. How this may affect individuals’ fuel stores and whether different biomes provide refuelling opportunities en route remains to be investigated, to understand how future land-use change may affect migration patterns and survival probabilities.

A comparative analysis and optimization of two supersonic hybrid SOFC and turbine-less jet engine propulsion system for UAV

In this study, we compared two different types of propulsion systems for a supersonic unmanned aerial vehicle (UAV) flying at Mach 1.8, which are using two different types of fuel to determine their characteristics and advantages. Also, investigate the effect of various factors such as altitudes and key design parameters of the propulsion system on efficiency and flight duration. These proposed propulsion systems are using a solid oxide fuel cell (SOFC) to generate the heat required for the operation of the turbine and generate thrust. The hydrogen for SOFC is either stored in the tank or generated by the internal reformation of methane inside the fuel cell. We studied the effects of several key design parameters for these engines in different flight conditions and altitudes; carrying out a multi-objective optimization for each proposed propulsion system to maximize the thrust of the engine while keeping the fuel consumption at a minimum rate to achieve the longest flight duration. Then we determined the best conditions where the acceptable thrust is accompanied by reasonable flight duration. Results indicated that the efficiency and generated power of the propulsion system will increase by higher flight altitude or compressor pressure ratio. Also, due to the recirculation of fuel in the SOFC’s anode, we observed higher efficiency in comparison when hydrogen is used; since anode-recirculation causes higher fuel utilization. The optimization result shows that the efficiency and fuel consumption for the hydrogen-fueled system is 48.7% and 0.0024 kg/s, respectively, and 67.9% and 0.0066 kg/s. for the methane-fueled engine.

РАСПОЗНАВАНИЕ ПОКАЗАНИЙ АНАЛОГОВЫХ ПРИБОРОВ НА ПРИМЕРЕ АВИАЦИОННЫХ ПРИБОРОВ ВЫСОТНО-СКОРОСТНОЙ ГРУППЫ

The article considers the issue of analog instrument reading using the example of high-altitude and high-speed flight instruments. The article provides a detailed description of the software that can read analog gauge data through the example of flight instruments during their verification. The article describes the main functions of computer vision library, image processing, and general-purpose numerical algorithms with open source (OpenCV), used for instrument readings. The software is developed in the high-level universal programming language Python 3.7.7. The results of the program are presented, showing this method performance of checking high altitude flight instruments.

Using High–Low Flight Gravity Data to Improve Geoid Model Precision: A Case Study in U.S. Virgin Islands (July 2021)

The Gravity for the Redefinition of the American Vertical Datum (GRAV-D) project collected airborne gravity data over Puerto Rico (PR) and the U.S. Virgin Islands (VI). There was one large N-S/E-W survey at about 11-km altitude running from N17 to N21 latitude and E291 to E297 longitude. Considering the very limited surface gravity coverage on VI, only about 500 points, additional flights were conducted at lower altitudes (1.5–1.8 km). By adding these additional low altitude aerial gravity data, the geoid model precision is improved from 6.55 cm with no airborne data to 2.55 cm with both the high and low altitude data. Using only the high altitude flights achieves only 4.99-cm geoid model precision. The ~500 surface gravity data points in the target area do not improve the model precision significantly, which justifies the rationale of carrying out these lower altitude flights. Noticing the nearly three times geoid model precision improvements from the low flight data, we suggest to fly in low altitudes in future airborne gravimetric survey for geoid modeling in the areas that have limited surface gravity coverage and/or small topographic features like islands that are not well-sampled in high-altitude, wider-spaced data.

Analysis and Verification of Aerodynamic Characteristics of Tianwen-1 Mars Parachute

The Mars parachute flight environment is supersonic, low-density, and low dynamic pressures. To ensure the operating performance and reliability, the design optimization and verification of the Tianwen-1 Mars parachute have been carried out. Firstly, through supersonic and subsonic wind tunnel tests, the design optimization of the parachute structure is realized. Subsequently, the high-altitude flight tests of four parachutes were conducted, the drag coefficient and the oscillation angle of the parachute from supersonic to subsonic speed were gained, and the aerodynamic characteristics and reliable opening of the parachutes were thoroughly tested and verified. This article presents the design, development, and qualification of the Tianwen-1 Mars parachute, which can provide a reference for the creation of future Mars exploration parachutes.

A Comparison of Three Airborne Laser Scanner Types for Species Identification of Individual Trees.

Species identification is a critical factor for obtaining accurate forest inventories. This paper compares the same method of tree species identification (at the individual crown level) across three different types of airborne laser scanning systems (ALS): two linear lidar systems (monospectral and multispectral) and one single-photon lidar (SPL) system to ascertain whether current individual tree crown (ITC) species classification methods are applicable across all sensors. SPL is a new type of sensor that promises comparable point densities from higher flight altitudes, thereby increasing lidar coverage. Initial results indicate that the methods are indeed applicable across all of the three sensor types with broadly similar overall accuracies (Hardwood/Softwood, 83–90%; 12 species, 46–54%; 4 species, 68–79%), with SPL being slightly lower in all cases. The additional intensity features that are provided by multispectral ALS appear to be more beneficial to overall accuracy than the higher point density of SPL. We also demonstrate the potential contribution of lidar time-series data in improving classification accuracy (Hardwood/Softwood, 91%; 12 species, 58%; 4 species, 84%). Possible causes for lower SPL accuracy are (a) differences in the nature of the intensity features and (b) differences in first and second return distributions between the two linear systems and SPL. We also show that segmentation (and field-identified training crowns deriving from segmentation) that is performed on an initial dataset can be used on subsequent datasets with similar overall accuracy. To our knowledge, this is the first study to compare these three types of ALS systems for species identification at the individual tree level.

Combined UAV‐ and tractor‐based stripe rust monitoring in winter wheat under field conditions

AbstractUnmanned aerial vehicles (UAVs) have the potential to monitor the health status of several crop fields of a farmer in full coverage. For a complete and fast monitoring, however, high flight altitudes are usually needed, especially if large areas should be observed in short time intervals. In this case, the resolution on the ground becomes insufficient to detect specific symptoms of crop diseases because a ground resolution in the submillimeter scale is needed. This study pursued the idea of performing remote UAV imaging to detect discoloration in combination with near‐surface tractor imaging to detect the uredospore layers as characteristic signs of stripe (yellow) rust (caused by Puccinia striiformis Westend. f. sp. tritici) in winter wheat (Triticum aestivum L.). To simulate healthy and diseased field parts, the 3‐yr experimental design included controlled infected plots and those sprayed with fungicides as healthy controls. Imaging, disease severity, and crop development rating were performed along a time series. Significant differences between infected and control plots occurred in the UAV imagery using the normalized green–red difference index from a median (upper three leaves) infested leaf area of 3% and for the tractor images using the maximally stable extreme regions detector from 3 and 5%, respectively. In the future, it is conceivable that farmers will combine UAV (aerial monitoring of crop damage of complete fields) and tractor (ground monitoring to determine the cause) imaging for automatic scanning of the health status.

Energy Depletion Guidance for Aerobraking Atmospheric Passes

An energy depletion guidance algorithm for shallow, high-altitude atmospheric flight, consistent with aerobraking atmospheric passes, is proposed. The guidance algorithm is based on optimal control solutions to the energy minimization problem and uses variable drag area for trajectory control achieved through articulated solar panels. The algorithm includes three control modes to limit heat rate, heat load, or both while attempting to maximize energy depletion. A closed-form approximate solution of the equations of motion for aerobraking atmospheric passes is used to generate steering commands in real time. Numerical simulation of aerobraking at Mars illustrates the performance of the algorithm modes for a range of initial conditions. Results indicate that the guidance algorithm increases nominal energy depletion by approximately 1600% relative to the uncontrolled case over a single aerobraking pass, equivalent to an increase in of approximately 1600%. Monte Carlo simulation analyses show that dispersed flight performance is consistent with nominal performance; the standard deviation of the depleted energy is at maximum 13.8% of the mean, and the maximum difference between the mean and the maximal energy depletion solution is lower than 1.4%.

Direct Aerial Visual Geolocalization Using Deep Neural Networks

Unmanned aerial vehicles (UAVs) must keep track of their location in order to maintain flight plans. Currently, this task is almost entirely performed by a combination of Inertial Measurement Units (IMUs) and reference to GNSS (Global Navigation Satellite System). Navigation by GNSS, however, is not always reliable, due to various causes both natural (reflection and blockage from objects, technical fault, inclement weather) and artificial (GPS spoofing and denial). In such GPS-denied situations, it is desirable to have additional methods for aerial geolocalization. One such method is visual geolocalization, where aircraft use their ground facing cameras to localize and navigate. The state of the art in many ground-level image processing tasks involve the use of Convolutional Neural Networks (CNNs). We present here a study of how effectively a modern CNN designed for visual classification can be applied to the problem of Absolute Visual Geolocalization (AVL, localization without a prior location estimate). An Xception based architecture is trained from scratch over a &gt;1000 km2 section of Washington County, Arkansas to directly regress latitude and longitude from images from different orthorectified high-altitude survey flights. It achieves average localization accuracy on unseen image sets over the same region from different years and seasons with as low as 115 m average error, which localizes to 0.004% of the training area, or about 8% of the width of the 1.5 × 1.5 km input image. This demonstrates that CNNs are expressive enough to encode robust landscape information for geolocalization over large geographic areas. Furthermore, discussed are methods of providing uncertainty for CNN regression outputs, and future areas of potential improvement for use of deep neural networks in visual geolocalization.

Research on color coding of fighter jet head-up display key information elements in air–sea flight environment based on eye-tracking technology

HUD is currently the main flight status display commonly used in modern fighter jets. Color coding is an important method in HUD visual information display. Different weather, terrain, climate, time, season, and other environmental phenomena will affect the HUD. The HUD’s multi-color display mode has become a key method to solve the overload display of dynamic and static information in complex flight environments. This paper discusses the use of eye-tracking equipment to record eye movement experimental data using different HUD color schemes, as well as the correct rate and response time to complete the task, in order to evaluate the color combinations of different characters in different high-altitude and sea flight background conditions. Cognitive status was obtained by seven key eye movement indicators (average fixation time, first fixation duration, fixation ratio, fixation time ratio, fixation track length and lookback times, and pupil diameter) designed by color-coded dimensions to evaluate the key element information of the HUD: discernibility, which is related to average fixation time, duration of first fixation, and pupil diameter; perceptibility, which is related to gaze ratio, fixation time ratio, and other indicators; and accessibility, which is related to fixation track length and number of lookbacks. At the same time, the background color brightness interval that affects color matching was obtained, and five key information colors (K1(0, 100, 100), K2(30, 100, 100), K3(300, 100, 100), K4(330, 100, 100), and K5(60, 100, 100)) were selected for experimental exploration to obtain the best matching scheme for color coding of key elements of the HUD against different lightness backgrounds. The results indicate that against a flight background with ocean brightness, ranges are [1–20], [21–40], [41–60], and [61–99] and colors with hues of 30, 300, 60, and 300 are selected for the key information. Finally, the results give an improvement and optimization plan for the HUD. The research conclusion provides some guidance for HUD design and improvement for different flight backgrounds, and a reference for improving pilots' cognitive performance.