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USE OF SYNTHETIC VISION TO ENHANCE AIRPORT CAPACITY

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Title: USE OF SYNTHETIC VISION TO ENHANCE AIRPORT CAPACITY


1
USE OF SYNTHETIC VISION TO ENHANCE AIRPORT
CAPACITY
  • J. David Powell, Stanford University
  • Professor (emeritus)
  • Aero/Astro Dept.
  • Presented at the Lockheed Martin
  • Palo Alto Colloquia
  • October 5, 2006

2
AIR TRAFFIC GROWTH
  • Recent Eurocontrol study
  • Flights could double by 2025
  • Biggest 20 airports will be saturated 8 to 10
    hours per day
  • Biggest 60 airports will be congested
  • There is a 15 to 20 year lead time required to
    develop infrastructure
  • Problem is similar in the USA
  • Need to start now to avoid severe problems in 20
    years

3
Airspace System Capacity
  • For enroute, is determined today by
  • Radar accuracy
  • Altimeter accuracy
  • For the airports, is determined by
  • Usable number of runways
  • Total number of runways that are usable
  • Parallel runway spacing
  • Weather

4
Landing capacity of airports (1)
  • To increase capacity with current technology
  • Add runways at existing airports
  • Parallel runways must be 3400 - 4300 ft apart
  • Requires a lot of land area
  • Very difficult to acquire land (or fill the Bay)
  • Make more use of secondary airports
  • Add new airports
  • Very difficult to acquire land

5
Example SFO
3400 to 4300
6
Worldwide Runway Expansion Projects
7
14
6
5
1
33 Parallel Runways under Development or
Construction
Source www.airport-technology.com
7
Lambert Field, St. Louis 2006
http//www.lambert-pmo.org/about/phase1/map/id42.a
sp?m4
8
Lambert Field Land Acquisition
9
Landing capacity of airports (2)
  • This talk will describe technology that
  • Allows much closer spacing of parallel runways
    therefore
  • uses much less land area
  • easier to expand existing airports
  • easier to obtain land for new airports
  • Allows more use of existing parallel runways in
    bad weather

10
Technology Available
  • Global Navigation Satellite Systems (GNSS)
  • GPS (U.S.), Galileo (Europe), and Glonass
    (Russia)
  • Satellites in 20,200 km orbits, some elliptical
  • 10 15 m position accuracy - standard
  • 2 - 3 m 95 position accuracy differential
    (WAAS and EGNOS)
  • Automatic Dependent Surveillance Broadcast
    (ADS-B)
  • Air-to-Air and Air-to-Ground Datalink
  • Broadcasts aircraft position velocity, etc
  • Synthetic Vision shows
  • neighboring traffic
  • wake vortices from neighboring traffic

11
Wide Area Augmentation System (WAAS)
12
Automatic Dependent Surveillance-Broadcast (ADS-B)
  • Aircraft / vehicle broadcasts known GPS
    position and additional data with reception rate
    of once per second
  • ADS-B Message now includes
  • Lat/Lon, Altitude
  • Velocity
  • Intent
  • Call sign
  • Heading
  • Aircraft category

13
Comparision - Radar ADS-B
  • Courtesy FAA Air Traffic Organization

14
Long Range Radar vs. ADS-B
Courtesy FAA Air Traffic Organization
15
WAAS/EGNOS ADS-B Benefits
  • Compared to radar surveillance
  • Much greater accuracy
  • Faster update rate
  • Coverage requires a simple antenna
  • Much lower cost
  • Available to pilots as well as controllers
  • Traffic separation can be partly accomplished by
    pilots

16
Why 3400 -4300 ft runway separation now in bad
weather?
  • Accuracy of guidance from Instrument Landing
    System (ILS)
  • Accuracy and update rate of radar surveillance
  • Response time to alert pilot of a problem
  • Time for controller to recognize problem
  • Time to communicate to pilot via radio
  • Time for pilot to react to ATC instructions
  • Time for pilot and aircraft to execute escape
    maneuver

17
Design Principle
  • Pilots are able to land on very closely spaced
    runways in good weather now
  • at San Francisco, pilots routinely land on
    parallel runways separated by 750 ft
  • Therefore, make instrument flying like visual
    flying by highlighting the critical features of
    the outside scene on a cockpit display

18
Some Design Features
  • Use a perspective (pictorial) display of approach
    and traffic (Synthetic Vision)
  • Modify ADS-B for approach use so that
  • 1 sec update is guaranteed
  • Roll angle is broadcast
  • Add a depiction of the wake vortices of
    neighboring traffic
  • A feature not available in any weather now

19
Cockpit Displays
Current technology
Synthetic Vision
20
3D Perspective Display
Roll of Bogey
Ownship Roll
Groundspeed
Altitude
Parallel approach pathway
Horizon Line
Flight path vector
Final approach pathway
Bogey Aircraft
Distance to touchdown
Heading
Logo
21
Map Display
Warning Danger Zone
Bogey
Caution Danger Zone
Ownship
Approach Tunnels
22
Orthographic Display
Longitudinal Spacing Indicator
Ownship Tunnel
Bogey Tunnel
Ownship Position
Current Bogey Position and Roll
23
Mixed Display
24
Parallel Approach Flight Testing
25
System Architecture
Ownship (Caravan)
Bogey (Saratoga)
Attitude GIA2000
Position WAAS
ADS-B Datalink
Attitude Honeywell INS
Position WAAS
Display Computer Terrain Path- way Databases
ADS-B Datalink
LCD Flight Display
26
Longitudinal Station-keeping
Station-Keeping Error (nm)
Out the Window
Display
Approaches
27
Monte Carlo Simulation
  • Want to evaluate the probability of a Loss of
    Separation due to a blunder during Closely Spaced
    Parallel Approaches (CSPA).
  • 10,000 CSPA simulations per configuration of
    longitudinal spacing and reaction time.

28
Probability of Loss of Separation on CSPA vs
Longitudinal Spacing and Runway Spacing
FAA Safety Threshold 500 wingtip to wingtip
Probability of Loss of Separation on CSPA
1220
P(LOS) lt 5x10-10 for LS gt 2000
Runway Spacing (feet)
29
Sensitivities
Minimum Safe Runway Spacing (feet)
Wake Vortex
Wake Vortex
Longitudinal Spacing (feet) RT 0.4 to 4.4
seconds
  • Employ the benefits derived from controlling
    Longitudinal Spacing

30
What are wake Vortices?
31
Wake vortex effect on spacing
WIND
32
Effect of Wake on Safe Zone
Safe Zone
Danger Zones
Wake Vortex
WIND
33
Nominal Wake Model
zg
descent profile
xg
zw/g
zlimit
zw/g f(w, t)
w f(Wt, V, b, r)
Zlimit f(vortex instabilities, atm. conditions)
34
Wake Uncertainty Model
zg
xg
Flight path
Nominal wake depth
Uncertainty over time
35
Wake-Danger Zone Model
wake plane
1 sec
36
Piloted Flight Simulations
In-trail Encounter Scenario
KNUQ
37
Flight Test Aircraft
  • Five Pilots
  • Six Flights
  • Three Scenarios

38
Additional Test Equipment
Caravan (probe)
Video Recording Rack
Saratoga (lead)
39
Flight Test
In-trail Same Air Mass
Wake
Ground Track
Air Mass
40
Results
In-trail Same Air Mass
41
Results
In-trail Same Ground Track
42
Wake Vortex Flight Test Results
  • Subjective results established a proof of concept
  • The image on the display faithfully represented
    the view out the window
  • A wake-hazard zone appeared to reliably bound the
    wake hazard
  • Pilots reported they could discern no noticeable
    difference between the wake location and the
    display prediction
  • The wake display improved the awareness of the
    wake hazard
  • The pilots loved it, and wanted it ASAP

43
Conclusions (1)
  • Showed novel displays and supporting systems to
    solve issues related to airport capacity
  • Pilots can view neighboring traffic and its wake
  • Coupled with ADS-B, the displays have potential
    to reduce parallel runway spacing from 4300 ft to
  • 750 ft if lead aircraft can be positioned on
    downwind side
  • 750 ft if cross wind is less than 10 kts
    regardless of positioning
  • Allows more use of existing runways in bad
    weather
  • Reduces amount of land required for airport
    expansion
  • Reduces environmental impact of airport
    expansions
  • Improves political climate for airport expansions

44
Conclusions (2)
  • Much more development is needed
  • Implementation will not be easy
  • Requires extensive simulation
  • Requires extensive flight testing
  • Safety must be equal to or better than current
    system and procedures
  • Requires acceptance by all stakeholders
  • Alternative is to build new airports and/or
    runways with 3400 - 4300 ft separation.

45
Domestic Airports with Closely Spaced Runways
Newark Seattle Los Angeles San Francisco San
Jose Las Vegas
Detroit Salt Lake City Phoenix Tampa
Atlanta Houston Dallas-Ft. Worth Pittsburgh St.
Louis
Minneapolis Memphis Kennedy Raleigh-Durham
Boston Detroit Orlando
Data courtesy of C. Haissig, Honeywell
46
Acknowledgements
Dr. Sharon Houck Dr. Chad Jennings Dr. Wendy
Holforty
FAA SatNav Program Office
  • Flight Test Crew
  • Lee, Frank, Mohamad, Skander
  • Sky Research
  • Moffett Federal Airfield

GPS Lab Andy, Keith, Rodney
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