SBMDA Briefing (October 2013)

Transcription

Commercial Satellite Electro-Optic Imagery
for
Space Based Maritime Domain Awareness
October 2013
David L. Neyland, Associate Director
Office of Naval Research – Global
US Navy
London, UK
david.l.neyland.civ@mail.mil
Dr Nigel P. Bannister, Senior Lecturer
Department of Physics & Astronomy
University of Leicester
Leicester, UK
nb101@leicester.ac.uk
Any use or reuse of the material herein or distribution of such must attribute the study to the US Navy Office of Naval Research - Global and the University of Leicester, UK .
Distribution A: Approved for public release; distribution is unlimited.
The Problem
• Small vessels at sea may not be detectable by current land and
space-based approaches with AIS and/or SAR
• Space Based Maritime Domain Awareness (SBMDA) is recognized
Internationally as mutually beneficial
• Space-Based AIS data collection is becoming a commodity
• Demonstrations in 2006 and LiMES in 2010 successfully showed that
EO/IR can be used with AIS and SAR to identify and track vessels at
sea
• There is currently no approach or incentive to provide ubiquitous
commercial satellite ocean imagery for use in SBMDA
US National Space Policy - June 28 , 2010
Use Space for Maritime Domain Awareness
•
•
International Cooperation
– Departments and agencies, in coordination with the Secretary of State, shall:
•
Promote appropriate cost- and risk-sharing among participating nations in international partnerships; and
•
Augment U.S.capabilities by leveraging existing and planned space capabilities of allies and space partners.
Identify Areas for Potential International Cooperation. Departments and
agencies shall identify potential areas for international cooperation that may
include, but are not limited to: space science; space exploration, including human
space flight activities; space nuclear power to support space science and
exploration; space transportation; space surveillance for debris monitoring and
awareness; missile warning; Earth science and observation; environmental
monitoring; satellite communications; GNSS; geospatial information products and
services; disaster mitigation and relief; search and rescue; use of space for
maritime domain awareness; and long-term preservation of the space
environment for human activity and use.
Background: AIS
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The International Maritime Organization (IMO)
International Convention for the Safety of Life at Sea
(SOLAS), requires Automatic Identification System
(AIS) transponders to be fitted to:
– All ships >300 tons gross on international
voyages
– Cargo ships >500 tons on any route
– Passenger ships of any size built after 2002
AIS transmits identification, position, status (at
anchor/underway, etc.), heading, rate of turn…
AIS transmission is directly from vessel to shore, or
via relay (using transponders on nearby vessels) or
received using space-based AIS systems
Image: Courtesy of nauticexpo.com
4
Image: Courtesy of maritimejournal.com
Commercial space-based AIS = Solved
US Coast Guard AIS Data – 24 hours – 20 November 2011 – Courtesy
Navy Times, Jacqueline Klimas, 3 June 2012
One week of data collected by University of Aalborg,
Denmark, AAUSAT3 – a student built and operated Cubesat
launched 25 February 2013 – Courtesy Jesper Larson,
Aalborg University, USN ONRG meeting 5 September 2013
• Another example, per Michael Jones, CTO, Google, Google uses two
SpaceQuest satellites which capture AIS data globally
• Google Earth is used for common Internet display of AIS data and there
are a multitude of commercial and amateur websites displaying AIS data
Why AIS Is Not Enough
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Only a small fraction of vessels (~200,000 of the
17,000,000 registered worldwide) are required to
carry AIS. Though some others carry voluntarily, the
majority of vessels are not AIS-equipped
AIS can be turned off, or “spoofed” to transmit
deliberately misleading information
–
•
Image: Courtesy of NauticExpo.com
E.g. Iranian tankers spoof AIS to conceal voyages into Syrian waters:
http://gcaptain.com/iran-falsifying-ais-data-to-conceal-ship-movements
Image: Courtesy of REUTERS / Tim Chong
Space-based AIS detection still limited by available
spacecraft, service levels, and limitations imposed
by current data protocol
–
E.g. Carson-Jackson, J., “Satellite AIS – Developing Technology or
Existing Capability?”, J. Navigation, 2012, 65, pp. 303-321
Images: Courtesy Jesper Larson,
Aalborg University, USN ONRG
meeting 5 September 2013
6
Synthetic Aperture Radar MDA
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Mainly L, C & X-band
Spatial resolution versus swath trade-off
– from 1-30 m for 30-100 km swath,
to 100-1000 m for 30-500 km swath
•
12 SAR spacecraft listed in Online Databases
Kompsat-5 (S.Korea)
RadarSat-2 (Canada)
COSMO-SkyMed (4 spacecraft, Italy)
RISAT-1 & 2 (India)
HuanJing-1 (China)
TerraSAR-X & TanDEM-X (Germany),
Meteor-M N1 (Russia)
•
Images: http://www.crisp.nus.edu.sg
Access to data is limited and tightly controlled
by the asset operators
The Electro-Optical SBMDA Concept
•
Imaging of Earth from space in the visible-IR band is
common
– At least 8 times as many EO sensors in Low Earth
Orbit compared to SAR instruments, with EO
resolutions in the 1 – 300 m range
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A large number of VIS-IR spacecraft generate
commercially available data (for free/fee)
Commercial imagery providers are currently undertasked for over-water locations
With coordination between operators, these satellites
could form a SBMDA “Virtual Constellation”
generating regularly updated information on locations
of maritime vessels
Google Image
from Bahamas
(small vessel
~15-20m)
– Questions: Availability, Shareability, Affordability, Utility
* ONRG / University of Leicester SBMDA Study, Dr Nigel Bannister – August 2013
8
The EO SBMDA Initiative
• Can we take advantage of the capabilities of commercial
satellite EO imagery of the open ocean:
– Whether collected today or not,
– Using crowd sourced development,
– In a Big-Data-Cloud,
– To determine vessel locations,
– To provide for Safety of Life at Sea.
Previous / Ongoing Discussions
•
Dr John Mittleman – NRL, Office of the DoD Executive Agent for Maritime Domain Awareness
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Greg Bader, Mike McGuinness, HQ USEUCOM/J8 S&T Advisors
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Giulio Busulini, Scientific Attache, Italian Embassy (DC)
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Richard (Rick) M. Williams , Counsellor, Defence R&D, Canadian Embassy (DC)
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Michael Jones (CTO), Vint Cerf (CTO), Google
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Dr Brian Young, Ralph Marrett, Defense Technology Agency, NZ
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Doreen Dyck, Defense Counsellor, Canadian Embassy (London)
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Guy Thomas – Chairman, Global Maritime Awareness Institute for Safety, Security & Stewardship, Taksha University
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Delcan Kirrane - EU Science: Global Challenges, Global Collaboration
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Chris Reynolds, Director, Irish Coast Guard
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William Arras, VP Government Programs, Digital Globe
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Dino Lorenzini, CEO, SpaceQuest
Initial Steps
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Engage University of Leicester to conduct a preliminary study
Define desired imaging parameters, such as “ground sample distance (GSD)
Define “commercially available” as applied to electro-optic satellite imagery
Identify EO-SBMDA assets, i.e., what commercially available electro-optic satellites
sources exist and their capabilities
Create an AGI System Toolkit (STK) model of a “virtual constellation” of
commercially available electro-optic satellites
Define a data collection test zone to explore with the STK model
Simulate collection of data against real-world vessel tracks
Determine the viability of output from the virtual constellation
For the context of this study, commercially available is defined as any electrooptical satellite sensor which generates data that can be accessed by the
international public, either as a free/open-source data product or as a paid-for
service, regardless whether the satellite is owned and/or operated by a nation-state,
non-government agency or commercial enterprise.
Identifying EO-SBMDA Assets
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Satellites identified through
regularly maintained online
resources and STK catalogue
For selection they must
– Carry a visible wavelength
sensor with GSD better than
350 m
– Generate data that is available
to the public “for free or for fee”
•
Key resources include OSCAR,
Committee on EO Satellites,
Space-Track, NASA-NSSDC and
EOPortal
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Resolution versus Image Detail
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Care is required when considering “resolution” – angular versus
spatial, Full Width Zero Maximum versus Full Width Half Maximum
National Imagery Interpretability Scale (NIIRS) rates the level of
information that can be extracted from an image
– Applied post-facto
– General Image Quality Equation can predict NIIRS score but requires
detailed information on sensor performance and post-processing not
available in this study
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A useful and commonly quoted value is Ground Sample Distance
(GSD):
– GSD is the distance between adjacent pixel centers projected
onto the target
Need to understand what this means in terms of detail levels and
the size of vessel which can be recovered
Example is a high-resolution aerial image of a vessel with known
dimensions and image properties, and resampled / rescaled to
illustrate the detail that can be obtained, under favorable conditions,
for a range of vessel sizes and sensor GSDs
From Zheng & Tidrow, Infrared Physics & Technology, 52,
2009, pp.408-411
Resolution versus Image Detail Example
Resampled
• Original aerial view of HMS Protector used as a test
image, with background area increased using cloning.
Original at
https://navynews.co.uk/archive/news/item/1271
• Initial results indicate that a GSD less than 33% of
vessel length required for detection
• Sensors with GSD up to 350 m (largest tanker)
included; detection may be possible in “ideal” conditions
Identifying EO-SBMDA Assets
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Current asset list includes 55 satellites
from 19 countries and agencies
These spacecraft carry a total of 85
sensors falling within the GSD /
information availability requirements
Satellites include research EO
spacecraft, commercial mapping
spacecraft, disaster monitoring,
meteorological and engineering
prototype spacecraft
All are in Low Earth, near-polar orbits
All but one are Sun-synchronous
GSD of EO-SBMDA Constellation Sensors
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85 sensors will be proposed in
the virtual constellation
All sensors operate in the
visible part of the spectrum
Most sensors also include NIRIR channels
– IR may be effective for night-time
tracking but the limitations are not
yet understood in this study
– For this study no IR observations
are assumed; all detections take
place during times when the Sun is
above the horizon for the target
location
Note: 350 m GSD is marginal as a SBMDA asset –
i.e., it provides ~one pixel detection of a big tanker
Suggested SBMDA Study Box
8 deg by 10 deg = ~250k sqnm
Suggested collection box from Dr Brian
Young, NZ Defense Technology Agency,
3/15/2013, as “everything has to go around
Cape Reinga (the northern-most tip of NZ) on
the way to Australia…this would also capture
merchant vessels crossing the Tasman and
cruising boats arriving in the Bay of Islands
(Oct to Dec timeframe), and would have a
high probability of capturing Navy inshore
patrol vessels.”
Study Test Zone
• Study area is a box of approximately 500 x
500 nautical miles and includes part of the
NZ Exclusive Economic Zone (NZEEZ)
• Bounded by coordinates
27S 169E
27S 179E
35S 169E
35S 179E
• Current model* based on 3 km (~1.9 mile)
granularity within test zone (significantly
smaller than sensor footprints)
Image: courtesy mfe.govt.nz
Example Satellite Pass
Example Swath ~9 nm Wide *
by 500nm traverse in <2 min
* GeoEye-1 Instrument/Product Description (Public Domain 2009) lists 15.2 km (~9 nm) swath width
Another Satellite Follows
And Another Pass
Time
Geo-temporal Coverage
Image strips from
different satellites
can be fused in a
time-phased
mosaic
Longitude
Buried in the
geo-temporal
mosaic are the
vessels tracks
This is what we need to store in the Cloud and let the crowds figure out how to process!
EO-SBMDA Virtual Constellation
85 electrooptical sources
from 19
countries*
One Day Coverage, Daylight Hours
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Model run over one period of
daylight, from 18:49 UT (Aug 1) –
05:17 UT (Aug 2)
Results show the form of coverage
over a typical day (since equator
crossing times of satellites are fixed)
Gap length estimations for 1-day
simulations describe the frequency
of coverage within a single period of
daylight (i.e. are not dominated by
night time outage)
One Day Coverage, Daylight Hours
Number of accesses
Total observing time
Max gap between observations
All Sensors
Only sensors with GSD of 30 m or better
Modeling Specific Vessel Contacts
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Using YotReps & AIS track histories from
sailwx.info, routes & movements of 9 “real”
vessels are included in the model
Tracks time-shifted so that all vessels enter
the test zone during the 9 day model period
All instances in which a vessel was within a
sensor field of view, inside the test zone,
when the Sun was above the horizon,
identified
Weather outages are not included at this
stage – “clear sky” conditions assumed
Vessel Contact Results
No night-time IR data used
Vessel enters
zone at night
All Sensors
GSD 150
GSD 50
GSD 25
Example Case: Niña
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85 year old, 21 metre-long US schooner Niña left Opua, NZ
North Island, May 29th 2013 for Newcastle, Australia (1500 mile
journey)
Estimated voyage duration 10 days (avg. 5.4 knots)
Last contact June 4th, 370 miles WNW Cape Reinga (northern
tip of the North Island) in 26’ seas, travelling at 4 knots, bearing
310º
Reported overdue 12 June, search efforts ended after
overflying 737,000 square nautical mile area
No further contact; vessel with 7 onboard presumed sunk
Carrying only manually activated emergency beacons
Ship5 in the SBMDA model represents a Niña-like voyage
leaving Opua for Newcastle at 12:00 UTC, August 1st 2013 at a
steady 4 knots
http://www.sailmagazine.com/nina
Nina modeled as Ship5 track in SBMDA STK model
Ship5 Contacts (one day of voyage)
Nina modeled as Ship5 track in SBMDA STK model
Potential contact for Beijing-1 of Ship5 track in SBMDA STK model
500 km
Approx 26 km
OceanSat-2
Direction of motion
NigeriaSat-X
Terra
Deimos-1
FengYun 3A
& Landsat-8
Terra
Meteor M N1
Beijing-1
Rapideye-4
Numbers indicate GSD of observing satellite
NZEEZ
SBMDA
Test Area
Ship5 Contacts (as a function of GSD)
Approx 560 km
Max distance without contact: 132 km
All Sensors
GSD < 100 m
GSD < 25 m
GSD < 200 m
GSD < 50 m
GSD < 7 m
How Much Data?
•
The University of Leicester study computed the volume of data (bytes of imagery)
for the original study area
– Simplified approach based on RapidEye Specification (available online) –
scaled for others using their specs
– RapidEye imager generates a footprint with a cross-track dimension of
approximately 77 km, and an along-track unit of length 25 km with a Ground
Sample Distance (GSD) of 6.5 m.
– The number of pixels in a 77 x 25 km image is (77 x 25) km2 / (6.5 x 6.5) m2 =
53,472,222
– The image product has a 16 bit depth, so a single 77 x 25 km image is
predicted to have a size of 16 x 53,472,222 = 855,555,556 bits or
approximately 102 Mbytes
– Rapideye quotes a single frame file size of 462 Mbytes for 5 wavebands, perband size of 462/5 = 92.4 Mbytes, or 91% of the value estimated above
How Much Data (continued)
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Along track and crosstrack footprint of all 85 sensors estimated
The swath length is divided by the sensor GSD to determine the number of pixels along-track
The number of pixels along-track is multiplied by the number of cross-track pixels = the total number of
pixels within the observed swath
Multiplying by the bit depth then provides an estimate of the size of the data product for that pass
Total data storage requirement is simply the sum of these data product sizes for each access of each
sensor
...etc.
Note: If at least one pixel is inside the test zone and the illumination conditions are
met for that pixel, then the entire field of view is recorded.
Data from Each Senor for Study Case
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Histogram showing the size of each access in terms of the number of bits which represent
the observed swath.
Daily data volumes for the simulation
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3.9 TB/ 9.5 days =
0.43 TB data per day
10-day data volume
is estimated to be
4.33 TB for the
~500nm x ~500nm
study area
EO-SBMDA Study - Preliminary Results
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55+ satellites from 19 countries carrying a total of 85 imaging sensors generate images
which are available commercially / internationally / publically for free or for fee
When combined, the high resolution (GSD ≤ 350 m) sensors on these satellites give
complete coverage of the test zone (and by inference most regions of Earth) in one day
Excepting vessels which enter the test zone only briefly (e.g. transit across a corner), at
least one position fix per day is observed
In several cases, two or more fixes are available, separated by an hour or more
In favorable situations 10+ fixes are available at useful resolution
Using a coordinated approach of a virtual constellation, the availability of geo-temporal
imagery over water could be significant for improving safety of life at sea
Significant cross-processing of the imagery is crucial to extract meaningful time-phased
information from the data
This study shows that there may be great benefit in building an international, open
collaboration between imagery providers, cloud storage and open source algorithm
development to translate the potential collection of open ocean imagery into a meaningful
maritime domain awareness information
Where to Now?
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The study suggests that Commercial Satellite EO may provide sufficient data
(vessels contacts) to hypothesize vessels tracks – if the right algorithms existed
The intellectual issue is “how to derive tracks from sparse data of unrelated
detections from unrelated sensors spread across time”
The study is only a model of what satellites could collect – the challenge set
needs to be populated with real world imagery
Real world imagery would enable development of the algorithms to hypothesize
vessel tracks from geo-temporal, independent detections
The amount of imagery for ten days of collection from 85 sensors would be
~10-20 TB
Cloud Storage and Processing of the imagery is the only possible path to
developing algorithms
Data Collection Opportunity
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Sail to Fiji - June, 2014
– 20+ “small” sailboats
– ~1100 nm from Auckland,
NZ to Port Denarau, Fiji
Each sailboat will be equipped
with “Yellow Brick™ Iridiumbased Global Satellite Tracking
Characteristics and imagery of
all vessels documented a-priori
Provides a unique “truth case”
for EO imagery collection and
algorithm development
NZ DTA actively interested in
facilitating this as an experiment
Data Collection Area
for Sail to Fiji
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Original “Study Area” was ~500nm x ~500nm = ~250k square nm
To accommodate Sail to Fiji, Data Collection Area proposed to be ~500 nm by
~1260nm = ~668k square nm
Sail to Fiji
Data
Collection
Area
Original
Study
Area
Sail to Fiji Data
Collection proposed
to be bounded by
coordinates
17 S 170 E
17 S 180 E
38 S 170 E
38 S 180 E
Next Steps for ONRG – Possible Path
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Distribute the results from University of Leicester model of the time-phased satellite
coverage for the NZ collection zone – October-December 2013
Pool resources for a S/W Development Prize – November-December 2013
– Suggest $100k based on experience
Convince Owner/Operators to provide imagery for 8-14 days for “Sail to Fiji”
collection area – January-April 2014 (data collect June 2014)
Convince a “Cloud” owner/operator to provide data access, processing power and
connectivity – January-April 2014 (storage and processing June-October 2014)
Conduct Virtual Workshop via web and international location to present problem
and challenge to the research community – February-April 2014
Run the Algorithm Challenge in August-October 2014
Prize Award ~December 2014

SBMDA Briefing (October 2013)

Transcription

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