Ares I-X Trajectory Reconstruction: Methodology and Results

Karlgaard, Christopher D.; Beck, Roger; Derry, Stephen D.; Brandon, Jay M.; Starr, Brett R.; Tartabini, Paul V.; Olds, Aaron D.

doi:10.2514/1.a32345

Cited by 27 publications

(11 citation statements)

References 10 publications

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“…The reconstruction efforts sponsored by the MEDLI project have developed the methodologies to use onboard instrumentation including MEADS pressure measurements and the descent inertial measurement unit (DIMU) to reconstruct the MSL capsule entry as accurately as possible and to extract aerodynamic coefficients for comparison to preflight predictions. Karlgaard et al [9,10,11] have developed the MSL reconstruction methodology based on techniques developed for a number of recent flight projects, including Ares 1-X and Hyper-X. The reconstruction process and how the capsule state, aerodynamic performance and Mars atmosphere were reconstructed from inertial and pressure telemetry is described briefly below with details provided in cited papers.…”

Section: Methodsmentioning

confidence: 99%

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

Schoenenberger

Norman

Karlgaard

et al. 2014

Journal of Spacecraft and Rockets

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On August 5, 2012, the Mars Science Laboratory entry vehicle successfully entered Mars atmosphere, flying a guided entry until parachute deploy. The Curiosity rover landed safely in Gale crater upon completion of the Entry Descent and Landing sequence. This paper compares the aerodynamics of the entry capsule extracted from onboard flight data, including Inertial Measurement Unit (IMU) accelerometer and rate gyro information, and heatshield surface pressure measurements. From the onboard data, static force and moment data has been extracted. This data is compared to preflight predictions. The information collected by MSL represents the most complete set of information collected during Mars entry to date. It allows the separation of aerodynamic performance from atmospheric conditions. The comparisons show the MSL aerodynamic characteristics have been identified and resolved to an accuracy better than the aerodynamic database uncertainties used in preflight simulations. A number of small anomalies have been identified and are discussed. This data will help revise aerodynamic databases for future missions and will guide computational fluid dynamics (CFD) development to improved prediction codes.

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Section: Methodsmentioning

confidence: 99%

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

Schoenenberger

Norman

Karlgaard

et al. 2014

Journal of Spacecraft and Rockets

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“…Earth-GRAM 2007 was used to generate all atmospheric information, including standard deviations as a function of altitude [34]. This study also estimated that the atmospheric dispersions generated from Earth-GRAM could be reduced to 10% of their original dispersions through use of weather balloons to provide detailed day-of-launch atmospheric data [41]. Figure 10 shows the reduced atmospheric density and eastward and northward wind variation as a function of altitude for the nominal White Sands launch site.…”

Section: A Uncertainty Analysismentioning

confidence: 99%

Investigation of Drag-Modulated Supersonic Inflatable Aerodynamic Decelerators for Sounding Rocket Payloads

Miller

Steinfeldt

Braun

2015

Journal of Spacecraft and Rockets

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The goal of this investigation is to understand the sizing and performance of supersonic inflatable aerodynamic decelerators for Earth-based sounding rocket applications. The recovery system under examination is composed of a supersonic inflatable aerodynamic decelerator and a guided parafoil system to achieve sub-100 m miss distances. Three supersonic inflatable aerodynamic decelerator configurations (tension cone, attached isotensoid, and trailing isotensoid) are examined using the metrics of decelerator mass, aerodynamic performance, and vehicle integration. In terms of aerodynamic performance, the tension cone is the preferred choice for the sizes investigated. The attached isotensoid was shown to be the most mass efficient decelerator, whereas the trailing isotensoid was found to be the more ideal decelerator for vehicle integration. A three-degree-of-freedom trajectory simulation is used in conjunction with Monte Carlo uncertainty analysis to assess the landed accuracy capability of the proposed architectures. In 95% of the cases examined, the drag-modulated inflatable aerodynamic decelerator provides arrivals within the 10 km parafoil capability region, meeting the sub-100 m landed recovery goals. In 76% of the cases examined, the dragmodulated inflatable aerodynamic decelerator arrives within 5 km of this target zone. Nomenclaturenumber m = mass, kg q = dynamic pressure, N∕m 2 S = area, m 2 s = downrange, m T = reference temperature, K t = time, s u = eastward wind velocity, m∕s V = velocity, m∕s v = northward wind velocity, m∕s β = ballistic coefficient equal to m∕C D A, kg∕m 2 δDR = change in downrange, km λ = launch elevation angle, deg Subscripts D = drag deploy = deployment est = estimate f = areal max = maximum min = minimum para = parafoil ref = reference target = target

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Section: Introductionmentioning

confidence: 99%

“…Aiming to solve this problem, the fusion algorithms are studied based on the INS and FADS. Among these approaches, the complimentary filter method 20,22 and Kalman filter method [26][27][28][29][30][31] are the most common techniques. In complimentary filters, the low-frequency flow angles solved by the FADS are smoothed by that of the high-frequency results of the INS.…”

Section: Introductionmentioning

confidence: 99%

“…By contrast, the Kalman filtering approach can effectively estimate the trajectory parameters and the air data based on the fusion of the data of INS and FADS. Numerous researches [26][27][28][29][30][31] have presented and developed the Kalman filtering approach. Karlgaard et al [28][29][30][31] proposed a full state Kalman filters for estimating the trajectory parameters and the air data in Mars Science Laboratory Entry, Descent, and Landing Instrumentation (MEDLI) project.…”

Section: Introductionmentioning

confidence: 99%

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An implementation of the cubature Kalman filter for estimating trajectory parameters and air data of a hypersonic vehicle

Ding

Huan

Wang

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part G:

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Trajectory parameters (including the position, velocity, and attitude angles of a vehicle) and air data (consisting of the flow angles, the Mach number, and the freestream static pressure) are vital data for the analysis and evaluation process in the hypersonic flight tests. This paper describes a data fusion estimation algorithm for a flush air data sensing system/inertial navigation system/global positioning system integrated system, which is used to estimate the trajectory parameters and air data for an unpowered hypersonic vehicle. In the approach, the raw outputs of flush air data sensing system (i.e. the surface pressure measurements) are integrated with global positioning system results (the vehicle’s position and velocity) and inertial navigation system measurements (including the acceleration and the angular velocity measurements) by using a nonlinear Kalman filter algorithm. Firstly, the system state vector is defined with the trajectory parameters, the biases of the inertial sensors and the winds. Then, the system dynamic models are built based on the motion equations of an unpowered hypersonic vehicle, the inertial sensor error models and the wind model. Besides, the system measurement vector is designed with the global positioning system results and the flush air data sensing system raw outputs. Based on these works, the system state is directly estimated by using the cubature Kalman filter algorithm. After that, the air data is calculated based on the estimated values and a high-fidelity model of atmosphere. Simulation cases are implemented to assess the performance of the proposed algorithm. The results show that the proposed method could estimate the trajectory parameters and air data for hypersonic vehicle with a high precision.

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Ares I-X Trajectory Reconstruction: Methodology and Results

Cited by 27 publications

References 10 publications

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

Assessment of the Reconstructed Aerodynamics of the Mars Science Laboratory Entry Vehicle

Investigation of Drag-Modulated Supersonic Inflatable Aerodynamic Decelerators for Sounding Rocket Payloads

An implementation of the cubature Kalman filter for estimating trajectory parameters and air data of a hypersonic vehicle

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