Kevin Prosser (AF) Next-Next Gen Auto-GCAS

Kevin Prosser (AF) Next-Next Gen Auto-GCAS

Overview Introduction the Why? Test Item Description the What? Technology Developed the How? Test Execution Application of previous Lessons Learned Results 2

Auto-GCAS Safety & Program Lessons Applied Define Aggressive Recovery Validate the Recovery Maneuver and the Model Survey Test Area Terrain Develop Collision Geometry Add Terrain Buffer That Provides Adequate Available Reaction Time (ART) Get close to terrain only when required (build down required) Surrogate UAV (Safety Pilot monitoring Automated System) Safety Provided by Safety Pilot not by system under test Observe Detect Disengage W/ Available Reaction Time Maneuver 3

F-16 Auto-GCAS Architecture Aircraft State Aircraft Trajectory Prediction Predicted Trajectory Command Fly-up Coupler Navigation Solution Terrain Map Terrain Scanning Collision Estimation Simplified Terrain Profile Recovery Request Termination Angle As Fielded in 2013-2014 Modular but not portable! Flight Control Autopilot Notify Pilot

F-16 Auto-GCAS 5

Project Goals 1 - Transition and demonstrate the portability of the ACAT GCAS 2 - Develop and explore alternatives that might enhance the performance and portability of the system (for all A/C) SUAV Auto GCAS Program Objectives Vision Eliminate all present and future roadblocks (real and perceived) to Auto-GCAS implementation Address ALL potential limitations of current GCAS (F-16) DTED management (Pilot chore) DTED resolution (Limits Flight <300 AGL) Lateral escape (Limits Flight <300 AGL) Dispel Concerns about applicability to ALL Aircraft DTED Management/Resolution/Lateral Escape Trajectory Prediction Development Make Portability so easy, the pilot can do it 6

1 - Transition and demonstrate the portability: NASA DROID Dryden Remotely Operated Integrated Drone - SUAV Cloud Cap Piccolo II Autopilot Modified BTE Super Flyin King RC Plane FWD Looking Video Camera & L-band TX Desert Aircraft 11 HP 2 Cycle Laser Altimeter 80lb max TO Weight (with modified Gear) 85 knots Maximum Speed Pneumatic Disk Brakes 7

SUAV GCAS & Instrumentation Modifications Android Cradle/Interface HD Tail Camera Gumstix Computer (USB to Piccolo interface) Wiring harness Dedicated A123 battery for Gumstix (fwd bay) Switch for Gumstix power, plus battery recharging port Tail Structure Reinforced 8

Fixed Wing Spectrum F-16 Clean F-22 F-35 Climb C-17 B-52 T-38 F-16 Dirty Learjet T-6 Droid GA 0 True Airspeed (Inverse Turn radius) 800 9

DROID Control Safety Pilot 2.4 MHz RC (JR 12X) Piccolo Control 900 MHz Link (Autonomous, Cockpit, Direct) Nose Camera & HUD Full Maneuver Capability MQ-1 Performance Limits 10

SUAV Auto GCAS in Action 12

2 - Develop and explore alternatives that might enhance the performance and portability of the system (for all A/C) : Multi-trajectory escape predictions High Fidelity Encoding of DTED / Subscanning Hosting algorithms on low Cost Processors Kinematic Modeling of TPA 13

SUAV requires a lateral escape option Fighters: Great Climb Performance Even in IDLE Power! Poor Turn Radius (High True Airspeed) Targets (Cargo, GA, UAV ): Poor Climb Performance Even at Full Power! Good/Great Turn Radius (Med/Low True Airspeed) 14

Scan Pattern Differences rning Turning Circular 17

Multi-Trajectory Recovery Model Straight-climb and Leftclimb flyups not selected due to impending rocks Trajectory Prediction (TPA) at Flyup Initiation Run-in Line

Multi-Trajectory Advantages Allows low performance aircraft to terrain mask 270 climbing turning escape Box canyon mishap eliminated Eliminates bi-furcation of trajectory prediction much better fidelity of scan patterns & Improved Portability Reduces nuisance potential need three penetrations to trip a flyup vice just one (three bad DTED posts, 3 bad trajectory predictions, 3 bad nav solutions?) 19

DTED Resolution Induced Errors 6 arc-sec 20 3 arc-sec

Tip Tilt Terrain Encoding Accuracy based = Portable An Accuracy Based Method vice a Resolution Based Approach Max Error 22

High Fidelity Encoding of DTED Improved Portability Improved Accuracy No Pilot Workload 23

Direct Scan vs Subscanning Tip/Tilt can be Rastorized to any resolution desired* (Subscanning) (* even to a higher resolution than source) compressed cell data 1 1 3 3 3 3 2 2 2 1 e 11 e 12 e 13 e 21 e 22 e 23 e 31 e 32 e 33 e 41 e 42 e 43 e 51 e 52 e 53 e 61 e 62 e 63 e 71 e 72 e 73 e 81 e 82 e 83 e 91 e 92 e 93 e 101 e 102 e 103 1 1 3 3 2 3 3 1 2 2 F-16 DTED 3 arc-sec for GCAS & DTS Future: 6 arc-sec Map Shading 1 arc-sec near field GCAS 3 arc-sec mid field 12 arc-sec far field 1/3 arc-sec PR 24

Time (sec.) Decompression and Rasterization Statistics Sierra Mountain Cell Composed of 14303 tiles Cell levels from level 8 to level 18 Cell decompression time.0781sec Nellis AFB Range Cell Composed of 3530 tiles Cell levels from level 6 to level 18 Cell decompression time.0313 sec Tyndall AFB Range Cell Composed of 12 tiles Cell levels from level 2 to level 7 Cell decompression time.0156 sec Tip-Tilt Binarytree Decompression Cells Decompressed and Rasterized using Intel Core 2 Duo CPU T8300 @ 2.40GHz, All cells are binary tree tip-tilt All cells were rasterized to 512x512 posts or 7.03125 arc-second resolution 0.09 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 0 2000 4000 6000 8000 10000 12000 14000 16000 Tiles

Summary of CDM Advantages Real time decoding (hundreths of seconds) Insanely low memory size Increased accuracy Can specify the required accuracy Same database can be rasterized to any resolution for use on the same platform Same database can be used by multiple platforms or easily modified to meet individual needs Can carry the whole world (and the Moon and Mars if desired*) * Still room for family photos too Avoids the workload of routine DTED management No need to carry the DTED to the jet Avoids the off map mishap potential 26

Low Cost Processors Android Cell phone Why? Low cost Available & common Open Source Potential Warning only APP could be made available Multi-task environment (You do not need a dedicated AGCAS processor) Proves a point If you can host it in a phone Weight, Memory, Processor is NOT limiting 27

Fighters: Trajectory Prediction/Fly-up changes - Recovery dominated by roll rates/g and onset rate - GW, I xx variations extreme - May be flown in Idle - All envelope (speed & Attitude) Others: - Recovery dominated by P S - Some to no effect of rolling inertia - Must be flown at maximum Power - Limited Speed/attitude range 28

29

30

Kinematic Modeling Very Useful When Hi Fidelity Model Not Available Climb is a Ps Problem vice a g-onset/sustained Problem 31

SUAV Avoidance Maneuvers Straight: --Bank to wings level --Capture 1000 fpm climb --Capture 60 KIAS Left/Right: -- 40deg Bank -- Capture 800 fpm -- Capture 60 KIAS Application of AGCAS Lesson Learned: 1) Recovery Maneuver MUST be an Aggressive as defined by the operator A timely but weak recovery will be a Nuisance to the operator 2) Validated with Pilot Initiated flyups at altitude 32

Box Canyon Avoidance Maneuver Actual (MQ-9 Wingspan Red=Active Flyup Predicted 33

Contributing Factors: Small Vehicle Large/abrupt pitch up High Power VVI Command Climb No coord rudder P-Factor 34

Low Performance Challenges Application of AGCAS Lesson Learned: 1) Only go low when there is a technical reason 2) When you go low, build down incrementally Flyup Outside Scan Pattern Wind Measured Here 35

TPA Challenges Summary Winds higher percentage of True airspeed Varying Wind Gradient near terrain Vertical gust component significant P-factor can be significant (Low speed, climb power, pitch up) Unaddressed Problems (as of now) Performance varies day to day (no pax/full load) All aircraft unique (engine, wheel pants, prop ) 36

Test Execution: GCAS & Surrogate UAV Basics Validate maneuver & model Pilot initiated Recoveries at altitude Survey Terrain Test Objectives determine collision geometry Add Buffer to Digital Terrain to provide desired ART (Available Reaction Time = Low risk unless req d) Monitor run in Control room Real Time TSPI Ground Observers Safety Pilot (Observe, Detect, Disengage, Maneuver) Safety Pilot in position to recover at abort ART + Superior performance 37

Test Execution Safety Pilot Must be able to 1) Observe 2) Identify 3) Disengage 4) Maneuver 39

40

CFIT Mishap Scenarios Goal: Determine if Auto GCAS could have prevented historical CFIT mishaps Executed similar to any Collision Avoidance run TCB Build-down 2 UAV mishaps (MQ-1 and MQ-9) Conditions based on recorded mishap data 1 General Aviation mishap (Cessna T182T) Conditions based on mishap report Auto-GCAS Design Lesson: Keep design focused by testing it to actual mishap scenarios

Near Real Time Data Analysis: Flight 12 Card 3 Note: Terrain raised 100 ft to represent TCB = 0 Evaluate: TPA Digital Terrain Recovery Scan Pattern Patent Pending Is Actual trajectory within scan pattern?

Manned Fighter AGCAS Never used as mission enhancement Pilot always responsible for ultimate safety Evaluation Criteria Early activations (Nuisances) impede the pilot from executing an existing mission element Anxiety based offline metric is applicable UAV AGCAS It is intended as a mission enhancement Safety does not rely solely on pilot s ability to see the ground and avoid it (DTED/Maps used vice camera) If the mission couldn t be done without the AGCAS, how can any activation be too early Anxiety based metric not applicable 46

Demonstrated Portability Summary Developed Several New Technologies to improve Auto-GCAS performance for all aircraft Multi-trajectory Kinematic TP Tip-tilt Digital Terrain Applied Previously Learned Auto-GCAS and Surrogate UAV principles Zero Mishaps & very few surprises Next Direct scanning of Digital terrain Integration with GA aircraft (Avionics & auto-pilots) 47

Next Gen Auto-GCAS Next-Next Gen Auto-GCAS Questions?