Flight Dataset Research Articles

Comparison of Statistical Estimation Techniques for Mars Entry, Descent, and Landing Reconstruction

Flight data from an entry, descent, and landing sequence can be used to reconstruct the vehicle's trajectory, aerodynamic coefficients, and the atmospheric profile experienced by the vehicle. Past Mars missions have not contained instrumentation that would allow for the separation of uncertainties in the atmosphere and the aerodynamic database. The 2012 Mars Science Laboratory took measurements of the pressure distribution on the aeroshell forebody during entry and allows freestream atmospheric conditions to be partially observable. Methods to estimate the flight performance statistically using onboard measurements are demonstrated here through the use of simulated Mars data. A range of statistical estimators, specifically the extended Kalman filter and unscented Kalman filter, are used to demonstrate which estimator best quantifies the states and the uncertainties in the flight parameters. The techniques demonstrated herein are planned for application to the Mars Science Laboratory flight dataset.

Time-Dependent Mars Entry Aeroheating Estimation from Simulated In-Depth Heat Shield Temperature Measurements

There are substantial uncertainties in the computational models currently used to predict the heating environment and the Thermal Protection System material response during Mars entry. Flight data are required to quantify and possibly reduce such uncertainties as well as improve current computational tools. The Mars Science Laboratory Entry, Descent, and Landing Instrumentation suite will provide a comprehensive set of flight data that will include subsurface temperature measurements of its Phenolic Impregnated Carbon Ablator heatshield at different locations. The purpose of this paper is to investigate the time-dependent estimation of Mars Science Laboratory surface heating from simulated Mars Science Laboratory Entry, Descent, and Landing Instrumentation temperature data using inverse methods in the presence of random and bias measurement and model errors. The surface heat flux is indirectly reconstructed by estimating the discretized heat transfer coefficient profile as a function of time. Whole-time domain least-squares methods in conjunction with the Tikhonov regularization technique are applied to this problem. The performance of the estimation methods and the accuracy of the reconstructed surface conditions are investigated under different types of errors in the measurements, such as random noise and thermocouple lag. Furthermore, the effect of material property bias on the estimation of surface conditions is also studied.

Sensitivity Analysis of Extended and Unscented Kalman Filters for Attitude Estimation

The extended Kalman filter (EKF) and unscented Kalman filter (UKF) for nonlinear state estimation with both additive and nonadditive noise structures are presented and compared. Three different Global Positioning System (GPS)/inertial navigation system (INS) sensor fusion formulations for attitude estimation are used as case studies for the nonlinear state estimation problem. A diverse set of actual flight data collected from research unmanned aerial vehicles was used as empirical data for this study. Roll and pitch estimation results were comparedwith independent measurements from amechanical vertical gyroscope to evaluate the performance. The performance of the EKF and UKF is compared in terms of noise assumptions, covariance matrix tuning, sampling rate, initialization error, GPS outages, robustness to inertial measurement unit bias and scale factors, and linearization. Similar sensitivity for this GPS/INS attitude estimation problem was found between the EKF and UKF for most cases. Small differences were seen between EKF and UKF for initialization error and GPS outages: the UKF was found to be more robust to inertial measurement unit calibration errors, and the EKF was determined to be more computationally efficient.

Fault diagnosis and monitoring of oscillatory failure case in aircraft inertial system

A method for oscillatory fault detection and isolation is presented and used to detect oscillatory failures of redundant aircraft sensors involved in the computation of flight control laws. The objective is to switch off the erroneous sensor and to compute a consolidated parameter using data from valid sensors, in order to eliminate any anomaly before propagation in the control loop. The benefit of the presented method is to improve the consolidation process with a fault detection and isolation approach when only few sources (less than three) are valid. Different techniques are compared to accurately detect any behavioral change of the sensor outputs. The approach is validated on a normalized real flight data set.

Flight-Test Evaluation of Sensor Fusion Algorithms for Attitude Estimation

In this paper, several Global Positioning System/inertial navigation system (GPS/INS) algorithms are presented using both extended Kalman filter (EKF) and unscented Kalman filter (UKF), and evaluated with respect to performance and complexity. The contributions of this study are that attitude estimates are compared with independent measurements provided by a mechanical vertical gyroscope using 23 diverse sets of flight data, and that a fundamental difference between EKF and UKF with respect to linearization is evaluated.

The use of meta-heuristics for airport gate assignment

Improper assignment of gates may result in flight delays, inefficient use of the resource, customer’s dissatisfaction. A typical metropolitan airport handles hundreds of flights a day. Solving the gate assignment problem (GAP) to optimality is often impractical. Meta-heuristics have recently been proposed to generate good solutions within a reasonable timeframe. In this work, we attempt to assess the performance of three meta-heuristics, namely, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and a hybrid approach based on SA and TS. Flight data from Incheon International Airport are collected to carry out the computational comparison. Although the literature has documented these algorithms, this work may be a first attempt to evaluate their performance using a set of realistic flight data.

Geolocation of Argus Flight Data

In this paper, we briefly describe the Argus spectrometer and its mission. We then focus on the process to determine the geolocation of the spectrometer's flight data. For the Canadian Advanced Nanospace eXperiment 2 (CanX-2) Argus flight, we have used Simplified General Perturbations 4 (SGP4) propagation for position determination. Two sets of flight data are presented as examples. We estimate the uncertainty in the geolocation of Argus data using this method and investigate potential improvements for future Argus flights.

Modeling the ascent of sounding balloons: derivation of the vertical air motion

Abstract. A new model to describe the ascent of sounding balloons in the troposphere and lower stratosphere (up to ∼30–35 km altitude) is presented. Contrary to previous models, detailed account is taken of both the variation of the drag coefficient with altitude and the heat imbalance between the balloon and the atmosphere. To compensate for the lack of data on the drag coefficient of sounding balloons, a reference curve for the relationship between drag coefficient and Reynolds number is derived from a dataset of flights launched during the Lindenberg Upper Air Methods Intercomparisons (LUAMI) campaign. The transfer of heat from the surrounding air into the balloon is accounted for by solving the radial heat diffusion equation inside the balloon. In its present state, the model does not account for solar radiation, i.e. it is only able to describe the ascent of balloons during the night. It could however be adapted to also represent daytime soundings, with solar radiation modeled as a diffusive process. The potential applications of the model include the forecast of the trajectory of sounding balloons, which can be used to increase the accuracy of the match technique, and the derivation of the air vertical velocity. The latter is obtained by subtracting the ascent rate of the balloon in still air calculated by the model from the actual ascent rate. This technique is shown to provide an approximation for the vertical air motion with an uncertainty error of 0.5 m s−1 in the troposphere and 0.2 m s−1 in the stratosphere. An example of extraction of the air vertical velocity is provided in this paper. We show that the air vertical velocities derived from the balloon soundings in this paper are in general agreement with small-scale atmospheric velocity fluctuations related to gravity waves, mechanical turbulence, or other small-scale air motions measured during the SUCCESS campaign (Subsonic Aircraft: Contrail and Cloud Effects Special Study) in the orographically unperturbed mid-latitude middle troposphere.

Natural History of Limacodid Moths (Zygaenoidea) in the Environs of Washington, D.C.

The moth family Limacodidae is notable for its fascinating larval stages, but with the exception of a few important pest species, the natural history of these moths is still poorly known. The goal of this project was to investigate the natural history of moths in the family Limacodidae, as well as a species in the related family Megalopygidae, from the metropolitan Washington, D.C. area. The specific objectives of this study were to (ordered by life cycle from adult to larva): 1) summarize data on the flight times of the adult moths; 2) investigate the oviposition behavior of female moths, specifically their tendency to lay eggs in clusters; 3) document the phenology and host associations of locally-collected larvae; 4) develop an accurate means for assessing larval developmental stage; and 5) determine whether larval growth and cocoon weight predict lifetime fitness for females. In an adult flight dataset that spans ∼130 years, we found significant interspecific variation in flight periods collectively encompassing a season running from April through November. Several pairs of sympatric congeners differed significantly in median flight times suggesting temporal niche separation. We found that for two of the species we studied, Acharia stimulea and Euclea delphinii, females laid eggs in clusters, but females of the other species mostly laid eggs singly. We generally found limacodid larvae from early June through October and most limacodid species were found as larvae on at least eight different host plant species, which supports the presumption that most species are generalists. For A. stimulea and E. delphinii larvae, we developed a set of equations so that we may estimate larval mass given larval body length, which allows us to estimate a larva's developmental stage in the field. Lastly, we found that for both A. stimulea and E. delphinii, there was a positive relationship between a female's cocoon mass and the number of offspring she produced the following year; thus, for these two limacodid species, cocoon mass is a predictor of lifetime fitness for females. Here we present all of the natural history observations and data that we have collected and analyzed from a variety of sources.

Unscented Kalman Filtering for Reentry Vehicle Identification in the Transonic Regime

Parameter identification methods for processing flight data are frequently used to validate and improve a preflight aerodynamic database and, specifically, to reduce the associated uncertainties. In this framework, the paper describes an identification methodology developed for the first flying test bed of the Italian Aerospace Research Center, a demonstrator of technologies relevant to future reusable launch vehicles. The analysis is focused on aerodynamic modeling of the reentry vehicle configuration in the transonic flow regime, in which flight control system performance is affected by a significant level of parameter uncertainty. The parameter estimation is formulated as a nonlinear filtering problem and solved through a multistep approach, in which the aerodynamic coefficients are identified first and, in a following phase, a set of model parameters is updated. In each step, an unscented Kalman filter is used as a recursive estimation algorithm. The methodology is applied to the flight data of the Dropped Transonic Flight Test mission of the vehicle, carried out during the winter of 2007. The reported results demonstrate the good characteristics of the technique in terms of convergence, reduction of uncertainty of the a priori aerodynamic model, and capability of extracting the information content from a rather limited set of flight data on vehicle response.

Overview of the Cranked-Arrow Wing Aerodynamics Project International

This paper provides a brief history of the F-16XL-1 aircraft, its role in the High-Speed Research Program, and how it was morphed into the Cranked-Arrow Wing Aerodynamics Project. Various flight, wind-tunnel, and computational fluid dynamics data sets were generated as part of the project. These unique and open flight data sets for surface pressures, boundary-layer profiles, and skin-friction distributions, along with surface flow data, are described and sample data comparisons are given. This is followed by a description of how the project became internationally known as Cranked-Arrow Wing Aerodynamics Project International and is concluded by an introduction to the results of a four-year computational predictive study of data collected at flight conditions by participating researchers.

In-Flight Vibration Monitoring of Aeronautical Structures

The development of an aircraft requires careful exploration of the dynamical behavior of the structure subject to aeroservoelastic forces. A combination of ground vibration tests and in-flight tests is used for this purpose. For both types of tests, various sensor data are recorded, typically from accelerometers. Based on these data, the aircraft dynamics are identified through modal analysis or structural identification. System identification and parameter estimation from flight data sets are considered and industrial application for modern flight vehicle design and certification is discussed.

Measurements of reactive nitrogen produced by tropical thunderstorms during BIBLE‐C

The Biomass Burning and Lightning Experiment phase C (BIBLE‐C) aircraft mission was carried out near Darwin, Australia (12°S, 131°E) in December 2000. This was the first aircraft experiment designed to estimate lightning NO production rates in the tropics, where production is considered to be most intense. During the two flights (flights 10 and 13 made on December 9 and 11–12, respectively) enhancements of NOx (NO + NO2) up to 1000 and 1600 parts per trillion by volume (pptv, 10‐s data) were observed at altitudes between 11.5 and 14 km. The Geostationary Meteorological Satellite (GMS) cloud (brightness temperature) data and ground‐based lightning measurements by the Global Positioning and Tracking System (GPATS) indicate that there were intensive lightning events over the coast of the Gulf of Carpentaria, which took place upstream from our measurement area 10 to 14 h prior to the measurements. For these two flights, air in which NOx exceeded 100 pptv extended over 620 × 140 and 400 × 170 km2 (wind direction × perpendicular direction), respectively, suggesting a significant impact of lightning NO production on NOx levels in the tropics. We estimate the amount of NOx observed between 11.5 and 14 km produced by the thunderstorms to be 3.3 and 1.8 × 1029 NO molecules for flights 10 and 13, respectively. By using the GPATS lightning flash count data, column NO production rates are estimated to be 1.9–4.4 and 21–49 × 1025 NO molecules per single flash for these two flight data sets. In these estimations, it is assumed that the column NO production between 0 and 16 km is greater than the observed values between 11.5 and 14 km by a factor of 3.2, which is derived using results reported by Pickering et al. (1998). There are however large uncertainties in the GPATS lightning data in this study and care must be made when the production rates are referred. Uncertainties in these estimates are discussed. The impact on the ozone production rate is also described.

Deep Impact: The Anticipated Flight Data

A comprehensive observational sequence using the Deep Impact (DI) spacecraft instruments (consisting of cameras with two different focal lengths and an infrared spectrometer) will yield data that will permit characterization of the nucleus and coma of comet Tempel 1, both before and after impact by the DI Impactor. Within the constraints of the mission system, the planned data return has been optimized. A subset of the most valuable data is planned for return in near-real time to ensure that the DI mission success criteria will be met even if the spacecraft should not survive the comet’s closest approach. The remaining prime science data will be played back during the first day after the closest approach. The flight data set will include approach observations spanning the 60 days prior to encounter, pre-impact data to characterize the comet at high resolution just prior to impact, photos from the Impactor as it plunges toward the nucleus surface (including resolutions exceeding 1 m), sub-second time sampling of the impact event itself from the Flyby spacecraft, monitoring of the crater formation process and ejecta outflow for over 10 min after impact, observations of the interior of the fully formed crater at spatial resolutions down to a few meters, and high-phase lookback observations of the nucleus and coma for 60 h after closest approach. An inflight calibration data set to accurately characterize the instruments’ performance is also planned. A ground data processing pipeline is under development at Cornell University that will efficiently convert the raw flight data files into calibrated images and spectral maps as well as produce validated archival data sets for delivery to NASA’s Planetary Data System within 6 months after the Earth receipt for use by researchers world-wide.

Modelling and simulation of aircraft turnaround operations at airports

A new approach for the investigation of aircraft turnaround operation performance at airports is proposed in this paper. A Markovian type simulation model is used to simulate operational uncertainties arising from aircraft turnaround operations. Monte Carlo Simulation techniques are implemented to carry out stochastic simulations in order to capture the stochastic effects of flight punctuality and operational uncertainties. Two sets of flight data collected in a period of three months from a European airline are used in case studies. Simulation results, when compared with observations, show the close relationship between the departure punctuality of a turnaround aircraft and the length of scheduled turnaround time of an aircraft. It is concluded that the inherent schedule punctuality of a flight schedule is influenced by two factors: the amount of schedule buffer time included in the ground time of an aircraft and the operational efficiency of the turnaround. In addition, the proposed aircraft turnaround model is also a suitable managerial tool for airlines and aircraft ground service providers to evaluate the operational efficiency of turnaround operations.

On-line aircraft parameter identification using fourier transform regression with an application to NASA F/A-18 harv flight data

This paper applies a recently developed on-line parameter identification (PID) technique to sets of real flight data and compares the results with those of a state-of-the-art off-line PID technique. The on-line PID technique takes Linear Regression from Fourier Transformed equations and the off-line PID is based on the traditional Maximum Likelihood method. Sets of flight data from the NASA F/A-18 High Alpha Research Vehicle (HARV) aircraft, which has been recorded from specifically designed maneuvers and used for off line parameter estimation, are used for this study. The emphasis is given on the accuracy and on-line measure of reliability of the estimates. The comparison is performed for both longitudinal and lateral-directional dynamics for maneuvers at angles of attack ranging α=20δ through α=40δ. Results of the two estimation processes are also compared with baseline wind tunnel estimates whenever possible.

Satellite attitude determination based on GPS signal-to-noise ratio

A method is presented for coarse attitude determination using the Global Positioning System (GPS) signal-to-noise ratio (SNR) from a single antenna mounted on a near-Earth satellite. It comprises a calibration procedure and a single-point optimal solution for the orientation of the antenna boresight vector. The calibration step creates an empirical mapping of the SNR to the angle between the antenna boresight and the GPS line-of-sight vector, based upon a ground or flight data set. The rms attitude accuracy at the level of 3/spl deg/-10/spl deg/ is demonstrated with actual flight data from several spacecraft. Performance is shown to depend strongly on the number of GPS signals available and the quality of the calibration mapping function. The method is suitable as a backup attitude sensor for low-cost satellite and terrestrial applications, and as a coarse reference for ambiguity resolution and integrity verification of phase-based GPS attitude-determination algorithms.

Adaptive SNR-based carrier phase multipath mitigation technique

An improved technique that mitigates specular multipath in Global Positioning System (GPS) differential carrier phase measurements is described. It adaptively estimates the spectral parameters (frequency, amplitude, phase offset) of multipath in the associated signal-to-noise ratio (SNR), and then constructs a profile of the multipath error in the carrier phase. A multipath correction is subsequently made by subtracting the profile from the actual phase measurement data. The technique is demonstrated on ground based experimental data, as well as flight data from the atmospheric research satellite CRISTA-SPAS. Ground experiments were conducted on static platforms in severe multipath environments. Multipath was deliberately introduced by either strategic placement of reflectors or electronic injection. This allowed for some control over the strength and frequency of the multipath. Averaging the results from 43 ground and 18 flight data sets, the differential carrier phase multipath was reduced by 47%. The complete results for both ground and flight tests are presented and are accompanied by discussions of individual cases.

Comparative solar EUV flux for the San Marco ASSI

The Airglow and Solar Spectrometer Instrument (ASSI) on the San Marco D/L satellite has measured solar extreme ultraviolet irradiances. The data are currently being released for analysis. As a preliminary step in evaluating this important dataset, modeled solar irradiances from 4 to 105 nm are presented for comparison to the San Marco data. The comparable flux for March–December 1988 is obtained from a revised and extended empirical solar extreme ultraviolet model derived from OSO 1, OSO 3, OSO 4, OSO 6, AEROS A, and AE-E satellite and six rocket flight datasets. Model wavelength intervals having the highest photon flux include the 15–35 and 85–105-nm ranges. Solar rotational features are prominent on several occasions in the model time series. A useful example is the modeled integrated flux between 30–31 nm which includes the Si XI (30.3-nm) and He II (30.4-nm) irradiance. The modeled flux in this 1-nm range shows both an absolute 22% increase from beginning to end of mission and a solar rotational variability with a typical peak-to-valley ratio of 14%. The absolute modeled irradiance in this wavelength interval is 9 × 10 9 photons cm −2 s −1 ±35%.