Matthew J. Rebholz 27 October 2015 Small Airport Surveillance Sensor (SASS) Distribution Statement A. Approved for public release; distribution is unlimited. This work is sponsored by the Federal Aviation Administration under Air Force Contract #FA8721-05-C-0002. Opinions, interpretations, recommendations and conclusions are those of the author and are not necessarily endorsed by the United States Government. Sponsor: Matthew Royston, ANG-C52, Surveillance Branch (Andras Kovacs, Manager)
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Matthew J. Rebholz
27 October 2015
Small Airport Surveillance Sensor (SASS)
Distribution Statement A. Approved for public release; distribution is unlimited.
This work is sponsored by the Federal Aviation Administration under Air Force Contract #FA8721-05-C-0002. Opinions, interpretations, recommendations and conclusions are those of the author and are not necessarily endorsed by the United States Government.
Sponsor: Matthew Royston, ANG-C52, Surveillance Branch (Andras Kovacs, Manager)
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 2 SDC 18 November 2014
• Overview
• System Design
• Initial Data Collections
• Summary
Outline
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 3 SDC 18 November 2014
• Runway incursions remain a serious issue at small airports
• Visual surveillance can be impaired by decreased visibility, weather, and terrain
• One-In-One-Out procedures during IMC impacts airport capacity
Surveillance gaps exist at many small airports
Low cost secondary surveillance solutions needed to fill surveillance gaps for small airports
Motivation
Serious Runway Incursions by Airspace Class (2013)
FAA Aviation Safety Information Analysis and Sharing (ASIAS) System
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 4 SDC 18 November 2014
Small Airport Surveillance Sensor (SASS) Architecture
• Provides secondary surveillance of airport surface and nearby airspace • Actively interrogates surface ATCRBS & airborne non-ADS-B aircraft • Receives & validates ADS-B position from 1090ES • Remote Unit can be at airport, TRACON, ARTCC or remote facility
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 5 SDC 18 November 2014
• GA airports with Class D airspace towers – 370 potential airports
• Non-towered airports with substantial traffic – 30 with 100,000+ operations per year
• Potential to fill surveillance not covered by FAA radars or ADS-B
– ADS-B mandate applies to Class B & C and above 10,000’
• Potential to integrate SASS with runway incursion safety logic
• Small footprint that can be located on airport property or deployed as a mobile system for special events
SASS Fills Unique Role
Target Airports
Key Benefits
SASS provides low-cost surveillance capability to either augment, or provide standalone, cooperative airport surface and terminal area airborne surveillance
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 6 SDC 18 November 2014
• Overview
• System Design
• Initial Data Collections
• Summary
Outline
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 7 SDC 18 November 2014
Surface Surveillance
Minimum Coverage Area1 10,000 ft long 2,000 ft wide
Position Error (1 σ) ≤ 30 ft
Airborne Surveillance
Range 20 nm Position Error (1 σ)2 ≤ 0.2 nm Range Resolution3 ≤ 60 ft
References: 1. Low Cost Ground Surveillance System (LCGS) Specification. 2. Required Surveillance Performance Accuracy to Support 3-Mile and 5-Mile Separation in the National Airspace System”, S.D. Thompson et al, MIT Lincoln Laboratory Project Report ATC-323,
November 2006. 3. Mode S Sensor Specification, FAA-E-2716, Federal Aviation Administration, 1985
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 8 SDC 18 November 2014
• Passive: Surface Surveillance of Mode S Squitters – Azimuth measurements from both SASS units define two lines of position, θ1 and θ2
– Time difference of arrival (TDOA) defines hyperbola (derived from tRx1 and tRx2) – Geolocation is a least-squares solution that provides best fit to measurements
• Active: Surface/Airborne Surveillance of ATCRBS/Mode S Interrogations – Azimuth measurement from one sensor defines one line of position, θ1 – Time of arrival (TOA) from interrogation and reply, tinterr, provides range – Intersection of both lines defines position
Surveillance Methodology
SASS1 SASS2
hyperbola
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 9 SDC 18 November 2014
Remote Unit
Maximum Likelihood Geolocation Estimate
SASS Sensor B SASS Sensor A
Geolocation Process
Calibration
Sensor B Model Parameters
AOA Surface AOA Surface
TDOA Surface Test Data:
I/Q Samples Test Data:
I/Q Samples
Sensor A Model Parameters
AOA = Angle of Arrival TDOA = Time Difference of Arrival
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 10 SDC 18 November 2014
Modeled Surface Surveillance Error (ft) (Hanscom Field in Bedford, MA)
SASS Sensor
SASS Sensor
Model Assumptions Range error: 10’ (1 σ)
Azimuth error: 0.4° (1 σ)
30’ position error or less over entire surface movement area
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 11 SDC 18 November 2014
Range [nm]
0 10 20 30 40 50 60
Cro
ss-r
ange
[nm
]
0
0.1
0.2
0.3
0.4
0.5Cross-Range Accuracy
Airborne Surveillance Predictions
Range [nm]
0 10 20 30 40 50 60
SNR
[dB
]
0
10
20
30
40
Detection Range
Secondary Surveillance Radar Range Equation
SNR Detection Threshold
Successful detection at 20 nm
Cross-range Accuracy Requirement
• Can successfully detect at 20 nm
• Assuming azimuth accuracy = 0.4º from surface model requirement, we can achieve 0.14 cross-range accuracy at 20 nm (within 0.2 nm airborne requirement)
Meets cross-range accuracy requirement
Cross-Range accuracy assuming azimuth
accuracy = 0.4º
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 12 SDC 18 November 2014
Range Requirements
SASS meets range requirements (10’ for surface and 60’ for airborne)
- Note: 1 ns timing error ≈ 1 ft range error
GPS Time - Hours in the Day
19.4 19.6 19.8 20 20.2 20.4 20.6 20.8
Est.
PPS
Erro
r [ns
]
-15
-10
-5
0
5
10
15
20Timing Error
Gps0: Mean = 2.5 ns, Var = 7.2 ns
Gps1: Mean = 2.4 ns, Var = 6.9 nsDifference: Mean = 0.7 ns, Var = 0.6 ns
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 13 SDC 18 November 2014
• Minimize Maximum Mainlobe Beamwidth
– Azimuthal or direction finding (DF) error proportional to mainlobe beamwidth
• Minimize Maximum Sidelobe
– Smaller sidelobes reduce signal ambiguities
• Design Optimization Technique
– Use Monte Carlo techniques to do sampled search of array configurations
– Choose array configuration which minimizes performance metric • Performance metric defined as width of
worst-case mainlobe with specified maximum sidelobe
SASS Array Design Criteria
Degrees Beam Pattern: Rectangular Coordinates
Loss
[dB
]
Beam Pattern: Polar Coordinates
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 14 SDC 18 November 2014
SASS Prototype Array Design
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 -0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8 Array Layout
Meters
Met
ers
Antenna Elements (Monopoles)
Ground Plane
• Small enough for transport and able to be mounted on mobile antenna tower – 5’ x 5’ ground plane
• No moving parts, minimize material cost – 8 elements
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 15 SDC 18 November 2014
Modeled SASS Array Response
Mainlobe Characteristics - Max MB = 8º - Azimuth accuracy = 0.16º Assuming 50:1 beamsplit Sidelobe Characteristics - Max SL = -0.2 dB
X [m]
-1 0 1
Y [m
]
-1
-0.5
0
0.5
1Symmetric Array
Mainlobe Characteristics - Max MB = 11º - Azimuth accuracy = 0.22º Assuming 50:1 beamsplit Sidelobe Characteristics - Max SL = -2.5 dB
X [m]
-1 0 1
Y [m
]
-1
-0.5
0
0.5
1SASS Array
Steering Angle [degrees]
High sidelobes
Narrow mainlobe
Modeled Array Beam Patterns
-150 -100 -50 0 50 100 150
-150
-100
-50
0
50
100
150 -10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0 dB
Steering Angle [degrees]
Narrow mainlobe
Low sidelobes
SASS meets 0.4º azimuth requirements and lower sidelobes help reject false target detections
Angl
e [d
egre
es]
Angl
e [d
egre
es]
Modeled Array Beam Patterns
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 16 SDC 18 November 2014
SASS Signal Processing Chain
Digital Signal
Processor
Timing Antenna (x8)
Item Unit Cost Total
Antenna (x8) - Monopole $100 $800
Amplifier - 8-Channel Amplifier $2000 $2000
Receiver (x8) - Ettus N210 Universal Software Defined Radio (USRP) $2200 $17,600
Timing - Trimble Thunderbolt E GPS Receiver $1000 $1000
Digital Signal Processor - Thinkmate Server $10,000 $10,000
$33,000
Simple processing chain and COTS equipment lead to low cost system
Amplifier Receiver (x8)
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 17 SDC 18 November 2014
SASS Sensor Prototype Hardware
Ettus OctoClock-G
Ettus N210 USRPs
Processing Server and Storage RAID
Extra OctoClock-Gs and USRPs for
future 1030 MHz processing
Cost: $33,000 Power Consumption: ~1200W Dimension: ~2’ W x 3’ H (~14U)
Antenna Array
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 18 SDC 18 November 2014
• Overview
• System Design
• Initial Data Collections
• Summary
Outline
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 19 SDC 18 November 2014
Hanscom Field Data Collection
Test vehicle with DGPS & transponder
SASS Sensor
MODSEF (1.3 nm away)
Truth sources: DGPS, Lincoln Mode S radar (MODSEF), ADS-B equipped targets of opportunity & video cameras
SASS Sensor Remote
Unit
ADS-B equipped aircraft
DGPS
Transponder Test Vehicle
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 20 SDC 18 November 2014
Hanscom Field Data Collection
SASS Sensor
SASS Sensor Remote
Unit
Phased Array
Phased Array
Cameras
DGPS Base
Station
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 21 SDC 18 November 2014
Flight Facility Tower Cab
• Used to simulate Hanscom (BED) tower – Situation & video displays placed in front of Hut window – Video cameras installed for surveillance verification – Similar view from Hanscom Tower nearby
View of airfield to North from Flight Facility tower cab
Master Processing CPU
Camera Display
Situation Display
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 22 SDC 18 November 2014
Initial Field Experiment
• Mean Error: 22.7 ft • Standard Deviation: 17.2 ft • RMS Error: 28.5 ft
Achieved Accuracy
• Preliminary results are within expected accuracy predicted by model
• Expect improved performance with the addition of a track filter and additional calibration data
0
30
60
90 Feet
Position Error at Hanscom Field
- - - Truth from DGPS
Position Error [ft]
0 50 100 150 200 2500
20
40
60
80Histogram of Position Errors
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 23 SDC 18 November 2014
Aircraft Target of Opportunity
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 24 SDC 18 November 2014
• Overview
• System Design
• Initial Data Collections
• Summary
Outline
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 25 SDC 18 November 2014
• Q2 FY16 – Add 1030 MHz processing for active geolocation
• Detection and demodulation • Interrogation/reply association
– Examine airborne surveillance performance
• Q3 and Q4 FY16 – Field demonstration with passive and active surveillance
Future Work
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 26 SDC 18 November 2014
• SASS provides low-cost secondary surveillance for small airports – Accurate surface surveillance (30ft) and airborne surveillance out to
20nm
• Key benefits – Improved controller traffic situation awareness – Support for automated runway incursion alerting
• Key design features
– Highly accurate, low-cost phased array – Low cost COTS signal processing equipment – State-of-the-art digital signal processing leveraged from DoD work – Low power and small footprint can support mobile applications
Summary
Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 27 SDC 18 November 2014
• FAA NextGen Surveillance Branch (ANG-C52) – Andras Kovacs, Matthew Royston, Amit Choudhri, & Rachel Groggel
• MIT Lincoln Laboratory SASS Team – Swaroop Appadwedula, Steve Campbell, Skip Copeland, Bob Downing,
Derek Espinola, Joe Finnivan, Gary Hatke, James Keefe, Jamie Pelagatti, Tom Reardon, Matt Rebholz, Gregg Shoults, Mike Spitalere & Loren Wood