Organizational Unit:

Space Systems Design Laboratory (SSDL)

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https://hdl.handle.net/1853/70747

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Organizational Unit

Daniel Guggenheim School of Aerospace Engineering

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1138

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Publication Search Results

Now showing 1 - 9 of 9

Statistical Entry, Descent, and Landing Performance Reconstruction of the Mars Science Laboratory

(Georgia Institute of Technology, 2014-01) Dutta, Soumyo ; Braun, Robert D.

The Mars Science Laboratory spacecraft landed an approximately 900 kg rover on Mars on August 5, 2012 while using the largest aeroshell and supersonic parachute ever utilized by a planetary entry mission. Similar to past Mars missions, the spacecraft recorded inertial measurement unit data and radar altimeter measurements during its descent through the Martian atmosphere, but its aeroshell was also instrumented with ush atmospheric data system sensors that captured the pressure distribution on the vehicle during hypersonic and supersonic flight regimes. The rich data set enabled a comprehensive post flight analysis of the vehicle's trajectory. This paper shows the vehicle's reconstructed trajectory, aerodynamics, and atmospheric conditions using several statistical estimation methods, specifically the Extended Kalman filter, Unscented Kalman filter, and adaptive filter. The statistical estimation methods allow for both state estimation and uncertainty quantification of model errors, which could improve design of future Mars entry missions.
Analytically-derived Aerodynamic Force Moment Coefficients of Resident Space Objects in Free-Molecular Flow

(Georgia Institute of Technology, 2014-01) Hart, Kenneth A. ; Dutta, Soumyo ; Simonis, Kyle R. ; Steinfeldt, Bradley A. ; Braun, Robert D.

Fast, high-fidelity trajectory propagation of objects in near-Earth orbits is a key capability for space situational awareness and mitigating probability of collisions on orbit. This high-fidelity analysis requires accurate aerodynamics prediction for objects in the free- molecular regime of flight, but most tools for aerodynamic prediction for this regime either are found using assumptions or are computationally intensive. Symbolic manipulation software can be used to analytically integrate expressions for pressure and shear pressure coefficients acting on a general body in free-molecular regime to derive aerodynamic force and moment expressions. The analytical aerodynamics prediction method is described and relations have been developed for the sphere, cylinder, panel, and rectangular prism. The NASA-developed Direct Simulation Monte Carlo Analysis Code is used to validate the analytical expressions and it is shown that expressions are accurate within 0.38%. These generalized analytic expressions in terms of angle of attack, sideslip angle, freestream conditions, wall temperature, and accommodation coefficients allow near-instantaneous computation of the rarefied aerodynamics and enables space situation awareness analysis.
Cramér-Rao Lower Bound Optimization of Flush Atmospheric Data System Sensor Placement

(Georgia Institute of Technology, 2013-08) Dutta, Soumyo ; Braun, Robert D.

Flush atmospheric data systems take measurements of the pressure distribution on the forebodies of vehicles and improve the estimate of freestream parameters during reconstruction. These systems have been present on many past entry vehicles, but design of the pressure transducer suites and the placement of the sensors on the vehicle forebody have largely relied on engineering judgment and heuristic techniques. This paper develops a ush atmospheric data system design methodology using Cramer-Rao lower bound optimization to define the smallest theoretical variance possible from the estimation process. Application of this methodology yields Pareto frontiers of possible optimal configurations and identifies the number of ports which serve as the point of diminishing returns. The methodology is tested with a simulated Mars entry, descent, and landing trajectory.
Preliminary Statistical Trajectory Atmosphere Reconstruction of MSL Entry Descent Landing

(Georgia Institute of Technology, 2013-02) Dutta, Soumyo ; Braun, Robert D.

On August 5, 2012, the Mars Science Laboratory spacecraft landed the heaviest payload on Mars using the largest aeroshell and supersonic parachute ever used by a planetary entry mission. Moreover, an innovative Sky Crane landing system was utilized to softly and accurately place the science payload on the ground near the desired target. The spacecraft recorded inertial measurement unit data and radar altimeter measurements during its descent through the Martian atmosphere and the aeroshell was also instrumented with flush atmospheric data system sensors that allow for the reconstruction of the vehicle's pressure distribution and freestream atmospheric conditions. This paper shows the preliminary results of the vehicle's trajectory and atmosphere reconstruction using a statistical estimation methodology that utilizes an extended Kalman filter. This method has been demonstrated with simulated Mars entry data in the past, and has the capability of simultaneously estimating the parameters and their uncertainties using the initial state covariance and measurement uncertainties.
Uncertainty Quantification for Mars Entry, Descent, and Landing Reconstruction Using Adaptive Filtering

(Georgia Institute of Technology, 2013-01) Dutta, Soumyo ; Braun, Robert D. ; Karlgaard, Christopher D.

Mars entry, descent, and landing (EDL) trajectories are highly dependent on the vehicle's aerodynamics and the planet's atmospheric properties during the day-of- flight. A majority of previous EDL trajectory and atmosphere reconstruction analyses do not simultaneously estimate the flight trajectory and the uncertainties in the models. Adaptive filtering techniques, when combined with the traditional trajectory estimation methods, can improve the knowledge of the aerodynamic coefficients and atmospheric properties, while also estimating a realistic confidence interval for these parameters. Simulated datasets with known truth data are used in this study to show the improvement in state and uncertainty estimation by using adaptive filtering techniques. Such a methodology can then be implemented on existing and future EDL datasets to determine the aerodynamic and atmospheric uncertainties and improve engineering design tools.
Atmospheric Data System Sensor Placement Optimization for Mars Entry, Descent, and Landing

(Georgia Institute of Technology, 2012-08) Dutta, Soumyo ; Braun, Robert D. ; Karlgaard, Christopher D.

The Mars Science Laboratory (MSL) contains an atmospheric data system that takes measurement of the pressure distribution on the entry body during the hypersonic and supersonic descent phases of the flight. This pressure data can be combined with other on- board sensors, such as accelerometers, gyros, and radar altimeter, to estimate the flight's trajectory, aerodynamics and the atmospheric profile. The number of sensors and their locations for the atmospheric data system can be optimized to increase the accuracy of the post-flight reconstruction. Methodologies based on using the estimation residual and a surrogate of the observability matrix are presented here and results of the optimization exercises for pressure transducer systems on Mars entry, descent, and landing (EDL) vehicles are shown. These techniques can be subsequently applied in the design of instrumentation suites of future EDL vehicles.
Integrated Trajectory, Atmosphere, and Aerothermal Reconstruction Methodology Using the MEDLI Dataset

(Georgia Institute of Technology, 2012-06) Dutta, Soumyo ; Mahzari, Milad ; White, Todd R. ; Braun, Robert D.

The Mars Science Laboratory (MSL) mission’s instrumentation will enable accurate reconstruction of the vehicle’s entry, descent, and landing (EDL) performance including the trajectory, the observed atmosphere, aerodynamics, aeroheating, and heatshield material response. The objective of this paper is to develop methodologies for an integrated approach to the reconstruction of the vehicle’s EDL performance. Two estimation approaches are presented: Serial and Concurrent. The serial approach is demonstrated by application to the Mars Pathfinder flight data and estimating trajectory and aeroheating performance.
Comparison of Statistical Estimation Techniques for Mars Entry, Descent, and Landing Reconstruction from MEDLI-like Data Sources

(Georgia Institute of Technology, 2012-01) Dutta, Soumyo ; Braun, Robert D. ; Russell, Ryan P. ; Clark, Ian G. ; Striepe, Scott A.

Flight data from an entry, descent, and landing (EDL) sequence can be used to reconstruct the vehicle's trajectory, aerodynamic coefficients and the atmospheric profile experienced by the vehicle. Past Mars missions have contained instruments that do not provide direct measurement of the freestream atmospheric conditions. Thus, the uncertainties in the atmospheric reconstruction and the aerodynamic database knowledge could not be separated. The upcoming Mars Science Laboratory (MSL) will take measurements of the pressure distribution on the aeroshell forebody during entry and will allow freestream atmospheric conditions to be partially observable. This data provides a mean to separate atmospheric and aerodynamic uncertainties and is part of the MSL EDL Instrumentation (MEDLI) project. Methods to estimate the flight performance statistically using on-board measurements are demonstrated here through the use of simulated Mars data. Different statistical estimators are used to demonstrate which estimator best quantifies the uncertainties in the flight parameters. The techniques demonstrated herein are planned for application to the MSL flight dataset after the spacecraft lands on Mars in August 2012.
Statistical Entry, Descent and Landing Performance Reconstruction of the Mars Phoenix Lander

(Georgia Institute of Technology, 2011-06) Dutta, Soumyo ; Clark, Ian G. ; Russell, Ryan P. ; Braun, Robert D.

The Phoenix Lander successfully landed on the surface of Mars on May 25, 2008. During the entry, descent and landing (EDL), the vehicle had instruments on-board that took sensed acceleration, angular rates and altimeter measurements. In this study, methodology used to reconstruct the trajectory and other EDL performance information using a statistical filter to process the observations from the sensors is demonstrated. A statistical filter estimates parameters simultaneously with the uncertainty in the estimates. The results presented here will include Phoenix’s event timeline, trajectory information, time-of-flight atmosphere and aerodynamic coefficients of an EDL subsystem as well as the uncertainty in the estimated states.