scholarly journals Mars Entry Atmospheric Data System Trajectory Reconstruction Algorithms and Flight Results

2013 ◽  
Author(s):  
Chris Karlgaard ◽  
Prasad Kutty ◽  
Jeremy Shidner ◽  
Mark Schoenenberger ◽  
Michelle Munk
Keyword(s):  
Data System ◽  
Reconstruction Algorithms ◽  
Trajectory Reconstruction ◽  
System Trajectory ◽  
Atmospheric Data

Mars Science Laboratory Entry Atmospheric Data System Trajectory and Atmosphere Reconstruction

2014 ◽  
Vol 51 (4) ◽  
pp. 1029-1047 ◽  
Author(s):  
Christopher D. Karlgaard ◽  
Prasad Kutty ◽  
Mark Schoenenberger ◽  
Michelle M. Munk ◽  
Alan Little ◽  
...  
Keyword(s):  
Data System ◽  
Science Laboratory ◽  
Mars Science Laboratory ◽  
System Trajectory ◽  
Atmospheric Data

scholarly journals Tianwen-1 Mars entry vehicle trajectory and atmosphere reconstruction preliminary analysis

Astrodynamics ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 81-91
Author(s):  
Haogong Wei ◽  
Wei Rao ◽  
Guangqiang Chen ◽  
Guidong Wang ◽  
Xin Zou ◽  
...  
Keyword(s):  
Preliminary Analysis ◽  
Inertial Measurement Unit ◽  
Data System ◽  
Measurement Unit ◽  
Reconstruction Process ◽  
Trajectory Reconstruction ◽  
Sensing System ◽  
Scientific Instrumentation ◽  
Aerodynamic Database ◽  
Vehicle Trajectory

AbstractThe Tianwen-1 Mars entry vehicle successfully landed on the surface of Mars in southern Utopia Planitia on May 15, 2021, at 7:18 (UTC+8). To acquire valuable Martian flight data, a scientific instrumentation package consisting of a flush air data system and a multilayer temperature-sensing system was installed aboard the entry vehicle. A combined approach was applied in the entry, descent, and landing trajectory reconstruction using all available data obtained by the inertial measurement unit and the flush air data system. An aerodynamic database covering the entire flight regime was generated using computational fluid dynamics methods to assist in the reconstruction process. A preliminary analysis of the trajectory reconstruction result, along with the atmosphere reconstruction and aerodynamic performance, was conducted. The results show that the trajectory agrees closely with the nominal trajectory and the wind-relative attitude. Suspected wind occurred at the end of the trajectory.

Optimization Design of the Flush Air Data System

2014 ◽  
Vol 533 ◽  
pp. 312-315 ◽  
Author(s):  
Qing Feng Zhang
Keyword(s):  
Information Fusion ◽  
Optimization Design ◽  
Static Pressure ◽  
Data System ◽  
Redundant Information ◽  
Sideslip Angle ◽  
Atmospheric Data ◽  
Sensor Information ◽  
Information Optimization ◽  
Aircraft Data

A new configuration of multi sensor flush air data system was proposed and the detecting principles of the flush air data system was discussed. A large number of redundant information pick up from multi sensors embedded in aircraft data system put forward the requirements of information optimization. Characteristic value of air data defined in this chapter meet the active control system of aircraft redundancy requirements of total pressure, static pressure, angle of attack and sideslip angle of atmospheric data, was the foundation of the multi sensor information fusion system.

Study of the Lyapunov Exponents in Heart Rate Variability Signals

1997 ◽  
Vol 36 (04/05) ◽  
pp. 274-277 ◽  
Author(s):  
A. Casaleggio ◽  
S. Cerutti ◽  
M. G. Signorini
Keyword(s):  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Lyapunov Exponents ◽  
Trajectory Reconstruction ◽  
Long Period ◽  
System Trajectory ◽  
Beat Heart

Abstract:Heart rate variability signals obtained from 24 h recordings are analyzed for normal and pathological subjects. This time series contains information about the autonomic nervous system action regulating the beat-to-beat heart rate. Nonlinear contributions to the long period variability have been assessed by the calculation of the entire spectrum of Lyapunov exponents, after the system trajectory reconstruction, starting from the original variability signal. The positivity of Lyapunov exponent values, obtained from an unknown process, can establish whether the structure generating it shows nonlinear chaotic characteristics. This is what happens for the cardiovascular signals. Moreover, the different values obtained for the Lyapunov exponents operate a classification among the considered pathophysiological cases.

Mars Entry Atmospheric Data System Modeling and Algorithm Development

2009 ◽  
Author(s):  
Roger Beck ◽  
Christopher Karlgaard ◽  
Stephan O'Keefe ◽  
Paul Siemers ◽  
Brady White ◽  
...  
Keyword(s):  
System Modeling ◽  
Data System ◽  
Algorithm Development ◽  
Atmospheric Data
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