I. Best Estimated Trajectory (BET) objective: a) Produce reconstructed trajectory of the PA-1 flight to understand vehicle dynamics and aid other post flight analyses. b) Leverage all measurement sources taken of vehicle during flight to produce the most accurate estimate of vehicle trajectory. c) Generate trajectory reconstructions of the Crew Module (CM), Launch Abort System (LAS), and Forward Bay Cover (FBC). II. BET analysis was started immediately following the PA-1 mission and was completed in September, 2010 a) Quick look version of BET released 5/25/2010: initial repackaging of SIGI data. b) Preliminary version of BET released 7/6/2010: first blended solution using available sources of external measurements. c) Final version of BET released 9/1/2010: final blended solution using all available sources of data

Beck, Roger

Karlgaard, Christopher

Kutty, Prasad

Noonan, Meghan

NASA Technical Reports Server

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The Best Estimated Trajectory Analysis 
for Pad Abort One 
Prasad Kutty, Meghan Noonan 
Analytical Mechanics Associates, Inc. 
NASA Dryden Flight Research Center, Edwards, CA 
Christopher Karlgaard 
Analytical Mechanics Associates, Inc. 
NASA Langley Research Center, Hampton, VA 
Roger Beck 
Analytical Mechanics Associates, Inc. 
Huntsville, AL 
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https://ntrs.nasa.gov/search.jsp?R=20110010892 2019-08-30T15:19:09+00:00Z
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PA-1 BET Overview 
•  Best Estimated Trajectory (BET) objective: 
–  Produce reconstructed trajectory of the PA-1 flight to understand 
vehicle dynamics and aid other post flight analyses 
–  Leverage all measurement sources taken of vehicle during flight 
to produce the most accurate estimate of vehicle trajectory 
–  Generate trajectory reconstructions of the Crew Module (CM), 
Launch Abort System (LAS), and Forward Bay Cover (FBC) 
•  BET analysis was started immediately following the PA-1 mission 
and was completed in September, 2010 
–  Quick look version of BET released 5/25/2010: initial repackaging 
of SIGI data 
–  Preliminary version of BET released 7/6/2010: first blended 
solution using available sources of external measurements 
–  Final version of BET released 9/1/2010: final blended solution 
using all available sources of data 
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NewSTEP 
•  Numerical approach used in STEP (Statistical Trajectory Estimation 
Program) applied extensively in 1960s-1980s (X-23A PRIME, Viking, 
Pioneer Venus, Shuttle) 
•  AMA developed NewSTEP with numerous enhancements including: 
–  MATLAB Based 
–  Additional Measurements 
–  Numerical Improvements 
–  Updated filters 
•  NewSTEP successfully used for trajectory reconstruction in recent 
flight projects: 
–  Mars Exploration Rover (MER) 
–  X-43A (Hyper-X) Mach 7 and Mach 10 Flights 
–  Ballistic range data reduction for CEV 
–  ARES-1X 
–  MSL MEADS 
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NewSTEP Flow Chart 
•  Based on Iterative Extended Kalman Filter (IEKF) code to compute optimal 
6-DOF trajectory based on all available measurements taken during flight 
•  IEKF is a recursive weighted least-squares estimation that optimally blends 
sensor data and mathematical models to produce minimum variance 
estimates of the system state and uncertainty 
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Sources of Measurement Data 
•  SIGIs provide primary source of acceleration and rate information 
used to derive a deterministic trajectory solution 
•  Measurements from SIGI-1 and SIGI-2 are filtered through low pass 
frequency algorithm before use in NewSTEP 
•  Additional external sources of data: 
–  Radar measurements taken by WSMR range assets 
–  Optical measurements taken by WSMR range assets 
–  Atmospheric model derived from day of flight balloon 
measurements (winds, pressure, density, temperature) 
–  Mass properties model derived from Abort Motor burn curve (AM 
mass known as function of time) 
•  FADS data measurements were unavailable at time of Final BET 
release 
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SIGI Data Acquisition 
•  Linear acceleration and angular rate measurements were taken from 
SIGI-1 and SIGI-2 using the Dryden Flight Data Archive System 
(FDAS) 
•  SIGI data recorded at 100Hz 
•  Acceleration data provided to NewSTEP was derived from recorded 
SIGI velocities through differentiation 
•  When integrated, derived accelerations provided a strong match to 
the SIGI navigated position solution 
•  Velocities were corrected for lever-arm offset between SIGI and 
center of gravity using the day of flight mass properties model: 
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Windowing Raw Data 
•  SIGI data filtered using a low-pass frequency domain filter 
•  Filtering technique applied using the System Identification Program for 
Aircraft (SIDPAC) toolbox 
•  Different regions of trajectory were filtered at different frequencies depending 
on dynamic behavior during region 
•  Retain dynamics of vehicle while filtering out acoustics, structural, sensor 
noise, etc. 
•  High dynamic windows: Ignition, Sep Events (LAS, Drogue, Main) 
•  Low dynamic windows: Reorientation, Under chutes 
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Transition Between Windows 
•  Fourier filtering method produces anomalous behavior at beginning 
and end of data 
•  To prevent undesired effects due to filtering, windows are overlapped 
and filtered data in overlapping region is computed by weighted 
average 
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Ignition Acceleration 
•  Filtering acceleration at ignition produced high frequency oscillations 
between 0.25 and 0.75 seconds 
•  Oscillations caused by the high filtering frequency required to capture 
the rise rate in x-body acceleration 
•  Undesired frequency content passed through filter as a result 
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Radar Measurement Data 
•  Fourteen track assignments via C-band ground based radars 
•  Three radars provided good track quality of the CM 
•  One radar provided good track quality of the LAS (10 sec after 
jettison) 
•  No radars adequately tracked the FBC 
•  Radar data at low elevation angles (liftoff and landing) were not used 
due to multipath errors 
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Optical Measurement Data 
•  Optical cameras tracked the LAV/CM flight for a majority of the 
mission 
•  As many as 10 tracking stations captured LAV/CM flight providing a 
highly accurate position solution with very low uncertainties 
•  Lever-arm offset correction was made to account for shift between 
optical tracking location and vehicle center of gravity 
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Final BET Results - LAV 
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Final BET Results - LAV 
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Final BET Results - LAV 
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Final BET Results - LAV 
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Final BET Results - CM 
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Final BET Results - CM 
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Final BET Results - CM 
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Final BET Results - CM 
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Summary Slide 
•  PA-1 BET provided high fidelity reconstruction of trajectory using all 
available sources taken onboard and externally 
–  SIGI sensor data 
–  Radar data 
–  Optical data 
–  Day of flight atmosphere model and mass properties model 
•  Sources of data not used: 
–  FADS 
–  Vibration accelerometers 
•  Comprehensive analysis and NewSTEP heritage provides strong 
confidence in final results 
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The Best Estimated Trajectory Analysis for Pad Abort One

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