© Fraunhofer FKIE
Enhanced Maritime Traffic Picture for the Canadian Arctic
Giulia Battistello*, Martin Ulmke*, Camilla Mohrdieck**
(*) Fraunhofer FKIE - Sensor Data and Information Fusion Department - Wachtberg, Germany
(**) Airbus Defence and Space - Data Fusion Concepts, Integration & Tests – Ulm, Germany
10th SECURITY RESEARCH CONFERENCE – Future Security
Berlin, 15 - 17 September 2015
© Fraunhofer FKIE
PASSAGES PROJECTProtection and Advanced Surveillance System for the Arctic: Green, Efficient, Secure
Canadian-German Partnership: July 2013 – June 2016
To specify the requirements and the modular architecture of aninnovative maritime system to support operations in Arctic waters with afocus on the Northwest Passage
© Fraunhofer FKIE
Case Study: Covert Monitoring Scenario (I)
Frobisher Bay & Hudson/Davis Straits
Frobisher Bay
Only waterway to Nunavut’s capital Iqaluit
120km length, [20-40]km width with several islands
Detailed charts not available
Presence of ice
Hudson and Davis Straits
fishing grounds
Illegal fishing activities
border crossings
Frobisher Bay
Davis Strait
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Case Study: Covert Monitoring Scenario (II)
Frobisher Bay & Hudson/Davis Straits
Problem: the compilation of maritime traffic picture – i.e. the basis forsafety and security applications – is limited by the scarceness/absence oflocal sensors.
Sensor data might be missing due to
Sensor limited performance or unavailability
Data transmission interruption
Data “blanking” or spoofing
Objective: Development of a monitoring service that guarantees anhigher update rate of vessel tracks trough a minimal deployment of newsensors
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Input Data Source – SAT-AISSatellite Automatic Identification System
-70 -69 -68 -67 -66 -65 -64 -63 -6260
60.5
61
61.5
62
62.5
63
63.5
64
Longitude [deg]
Latitu
de [
deg]
Real Data from Exact Earth
Cooperative Vessels
Vessel ID, Position, Velocity, SOG, COG, Heading, Timestamp, Type and more
Measurements come as bursts with inter-bursts of 90 mins
Discontinuous tracks
FishingPassengerCargoIce BreakerOil/Chemical TankerWarship
Time Window: 12-18.08.2013
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Input Data Source – SAT-SAR ImagesSatellite Synthetic Aperture Radar
Real Data from RadarSAT-2 and TerraSAR-X
Position, Heading, Length
Low satellite revisit time for continuous surveillance
False detections
Validated with SAT-AISNot validated
12.08.2013 22:13:02 UTC
13.08.2013 21:44:02 UTC
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Input Data Source – Passive Radar
Innovation Simulated Data from network of passive sensors that exploit signals
already present in the surveillance area as illuminators of opportunity
GSM base stations and/or VHF radio stations
Position, Velocity of moving vessels
Advantages
Reduced electro magnetic pollution
Reduced installation and maintenance costs
Not subject to authorization by safety authorities
Covert tracking >> detection of non-collaborative vessels (not equippedwith AIS or not using it)
TX1
TX2
RX1RX2
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Passive Radar Data Simulation Set Up
Sensors Definition
Generation of Detection
Probability Maps PD Maps
Passive Radar Measurements
Simulator
Target Tracker
Measurements
Tracks
Ground Truth
Measurement Errors
AoI
Sensors descriptionAoI
Analysis of maritime traffic through historical data
Identification of available transmitters (Txs)
Optimization of the bistatic passive radar geometry (Tx-Rx) >> maximization of the target detection capability (PD)
Simulation of passive radar measurementsand tracks
Sensors description
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Sub-Areas Definition (I)
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60.5
61
61.5
62
62.5
63
63.5
64
Longitude [deg]
Latitu
de
[d
eg]
Area #1
Area #2
Area #3
PassengerCargoTanker
TX6 GSM @1900MHz(4 real – 2 new)FoV = 120°
RX1 GSMField of View = 210°BW = 83.5KHzAngular Res = 3.2°
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Sub-Areas Definition (II)
-70 -69 -68 -67 -66 -65 -64 -63 -6260
60.5
61
61.5
62
62.5
63
63.5
64
Longitude [deg]
Latitu
de
[d
eg]
Area #1
Area #2
Area #3
PassengerCargoTanker
TX6 GSM @1900MHz(4 real – 2 new)FoV = 120°1 VHF @100MHz
RX1 GSM - 1 VHFField of View = 120° - 120°BW = 83.5KHz – 15kHzAngular Res = 3.2° - 10°
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Sub-Areas Definition (III)
-70 -69 -68 -67 -66 -65 -64 -63 -6260
60.5
61
61.5
62
62.5
63
63.5
64
Longitude [deg]
Latitu
de
[d
eg]
Area #1
Area #2
Area #3
PassengerCargoTanker
TX1 VHF @100MHzOmnidirectional
RX1 VHFOmnidirectionalBW = 15kHzAngular Res = 10°
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-69.2 -69 -68.8 -68.6 -68.4 -68.2 -68 -67.8 -67.6 -67.4
62.9
63
63.1
63.2
63.3
63.4
63.5
63.6
63.7
63.8
Lon [deg]
Lat
[d
eg
]
X [m]
Y [
m]
5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9
x 105
7
7.01
7.02
7.03
7.04
7.05
7.06
7.07
x 106
Target Tracking Results (I)
Simulation Parameters Target• RCS = 100 m2• Height = 20 m• MDV = 4 m/s • PFA = 10^-3
Ground TruthPR Tracks
Results• 5 Targets in the AoI in the time window• 42 track segments from Passive Radar
Detection Probability Map
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Target Tracking Results (II)
X [m]
Y [
m]
6.4 6.6 6.8 7 7.2 7.4 7.6 7.8
x 105
6.78
6.8
6.82
6.84
6.86
6.88
6.9
6.92
6.94x 10
6
Simulation Parameters Target• RCS = 100 m2• Height = 20 m• MDV = 4 m/s • PFA = 10^-3
Results• 15 Targets in the AoI in the time window• 33 track segments from Passive Radar
-66 -65.5 -65 -64.5 -64
61.2
61.4
61.6
61.8
62
62.2
62.4
62.6
Lon [deg]
Lat
[d
eg]
Ground TruthPR Tracks
Detection Probability Map
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Target Tracking Results (III)
X [m]
Y [
m]
6.6 6.8 7 7.2 7.4 7.6 7.8
x 105
6.68
6.7
6.72
6.74
6.76
6.78
6.8
6.82
6.84x 10
6
Simulation Parameters Target• RCS = 100 m2• Height = 20 m• MDV = 4 m/s • PFA = 10^-3
Results• 15 Targets in the AoI in the time window• 35 track segments from Passive Radar
-66 -65.5 -65 -64.5 -64 -63.5
60.2
60.4
60.6
60.8
61
61.2
61.4
61.6
Lon [deg]
Lat
[d
eg
]
Ground TruthPR Tracks
Detection Probability Map
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Data Fusion
Data Fusion step is required to process in a common framework the information from the heterogeneous data sources
DATA FUSION ENGINE
SAT-AIS Tracks
Passive Radar Tracks
SAT-SAR Detections
Enhanced Maritime Traffic Picture
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Data Fusion
Data Fusion step is required to process in a common framework the information from the heterogeneous data sources
DATA FUSION ENGINE
SAT-AIS Tracks
Passive Radar Tracks
Enhanced Maritime Traffic Picture
Not available for the selected regions
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Data Fusion Results (I)
Fusion of SAT-AIS tracks and Passive Radar tracks leads to higher update rate of vessel tracks >> vessel monitored for longer time window (red plots correspond to passive radar only observations)
Track segmentation?
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Data Fusion Results (III)
Data fusion allows improving track continuity
Target in AoI
Visibility PR Tracking Output
Data Fusion Output
5 5 42 Segments 37 Associated to 5 tracks + 5 Not associated
15 10 35 Segments 35 Associated to 10tracks
-68.5 -68.4 -68.3 -68.2 -68.1 -68 -67.9 -67.8 -67.7 -67.6
63.1
63.2
63.3
63.4
63.5
63.6
63.7
Lon [deg]
Lat
[deg
]
Ground TruthPR TracksFused TracksSAT-AIS
-66 -65.5 -65 -64.5 -64 -63.5
60.2
60.4
60.6
60.8
61
61.2
61.4
61.6
Lon [deg]
Lat
[d
eg]
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Conclusions
PASSAGES Project >> Enhanced Maritime Traffic Picture for the Canadian Arctic
Covert Monitoring Scenario as case study >> to develop a monitoring service that guarantees an higher update rate of vessel tracks trough a minimal deployment of new sensors
Satellite AIS tracks and SAT-SAR detections augmented by GSM/VHF based Passive Radar as innovative sensor
Non cooperative vessels
Fusion of heterogeneous sensor data leads to
Higher update rate of vessel tracks
Improved track continuity
© Fraunhofer FKIE
Thank you for your
attention!
Dipl.-Ing. Giulia Battistello
Department of Sensor Data and Information Fusion (SDF) Fraunhofer FKIE
Webpage: passages.ie.dal.ca
