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If you can’t get a bigger target…
Beyond TSPI: Using Data Fusion to
Combine Multiple Sources of
Live Fire Test Data to
Determine Aerodynamics and
Characterize Control Events
NDIA Joint Armaments Forum & Exhibition, May 14, 2014
Alan F. Hathaway
Arrow Tech Associates, Inc.
South Burlington, VT 05403
802-865-3460 x12
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If you can’t get a bigger target… Problem:
14 May 2014 NDIA Joint Armaments Forum & Exhibition 2
Ground-Based Instrumentation
– Doppler Radar
– Position Radar
– KTM Optical Cameras
– Etc.
On-Board Instrumentation
– GPS
– Accelerometers
– Sun Sensors
– Etc.
• TSPI: Time, Space, Position, Information
– Will Always Be Important in Live Fire Testing
• However, We Need to Look Beyond TSPI -> Data Fusion
– How To Make Best Use of all Available Live Fire Test Data?
– Multiple Instrumentation Sources
– Instrumentation May Only Cover Portion of the Flight
• Instrumentation Signal “Drop-Out”
Solution: Data Fusion of All Sources Combined With Parameter Identification
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If you can’t get a bigger target… Parameter Identification
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• Assume: System Model has unknown parameters influencing flight (Ballistic Flight or Guided Flight)
• Objective: Determine magnitude of unknown parameters to obtain simultaneous best fit all of the test data – Obtain flight simulation that matches observed flight path and dynamic
motion with minimum errors
– Compare predicted flight motion using standard equations of motion with measured motion, differentially adjust aerodynamics to minimize differences
Parameter Identification Provides Accurate Assessment from Largest Portions of Test Data
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If you can’t get a bigger target… Parameter Identification
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1. Process starts with the standard equations of motion and estimated initial conditions & aerodynamics
2. Develops partial differential equations for each test measurement and coefficient for a set of parametric equations
3. Performs numerical integration to obtain partial derivatives for each test measurement and coefficient
4. Differential correction equation from Taylor Expansion
5. Solves for aerodynamics & examines residuals, updates equations of motion & iterates until change in residuals is “zero”
• Using a sensitivity matrix, the most sensitive parameters “fit” first.
Parameter Identification Uses All Available Measurements
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If you can’t get a bigger target… Analysis Procedure
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• Preliminary Analysis – Data Screening (e.g. does data have large noise?)
– Estimates of Initial Velocity & Conditions (Gun QE & Azimuth of Fire)
– Estimates of Burn-On & Burn-Off times (if needed)
– Overlapping Sectional Fits of Complete Trajectory via Equations of Motion
– Axial Force & Spin vs. Time & Mach and/or Thrust vs. Time
• Parameter Identification – Complete Parameter Identification
• Four Degree of Freedom (for ballistic flights)
• Six Degree of Freedom (w/Control Forces; w/ On-board sensors only)
Data Fusion Analysis Procedure of all Measurements
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If you can’t get a bigger target… Examples
14 May 2014 NDIA Joint Armaments Forum & Exhibition 6
• 155mm Artillery
• Hydra 70 Rocket
• 120mm Mortar
• 105mm
Wide Range of Uses; Ballistic, Powered & Guided
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If you can’t get a bigger target… Ground-Based: Radar
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• Tracking Doppler Radars – Provides Radial Velocity, Azim. & Elev.
– “Behind the Gun” & “Down Range” Doppler
• Position Radar – Provides Range, Azim. & Elev.
Velocity-Time Data is Basis for Drag/Thrust Solution
Radial Velocity vs Time Fit Error 0.64 meters/sec
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If you can’t get a bigger target… Ground-Based: Radar plus KTM
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KTM Camera #2: Elev Fit Error 0.11 deg
KTM Camera #1: Elev Fit Error 0.29 deg
Simultaneous Reduction of Multiple Source of Data
Doppler Radar: Elev Fit Error 3.29 deg
Doppler Radar: Vel Fit Error 2.09 m/s
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If you can’t get a bigger target… On-Board: Magnetometers
14 May 2014 NDIA Joint Armaments Forum & Exhibition 9
Magnetometer Provides Yaw & Roll Angle Data
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If you can’t get a bigger target… On-Board: Accelerometers
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Accelerations & Angular Rates Provide Information about Normal Force Coefficient & Dynamic Stability
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If you can’t get a bigger target… Ground-Based: Radar plus KTM
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Data Fusion Can Help Overcome Poor Test Measurements
KTM #1: Elev Fit 0.08 deg KTM #2:
Elev Fit 0.10 deg
KTM #3: Elev Fit 0.16 deg
Doppler Radar: Elev Fit 2.24 deg
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If you can’t get a bigger target… Summary & Conclusions
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• Improved Data Fusion – Combining of sensor data from disparate sources
– Improved Fit Accuracy
– Use fewer KTM cameras to reduce test cost w/equivalent accuracy
• Feedback Loops Direct from Test to Design Activity – Aerodynamics
– Stability
– Control Systems, Guidance, and Sensors
• Tools Must be Adaptable – New data sources/instrumentation
– New control systems
Data Fusion of Data from Different Sources Gathered from Live Fire Testing Can Improve Both TSPI and Aerodynamics
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If you can’t get a bigger target… Contact Information
Alan F. Hathaway
Arrow Tech Associates, Inc.
South Burlington, VT 05403
802-865-3460 x12
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