Basal Ice Imaging Radar

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Basal Ice Imaging Radar

• Byrd Polar Research Center, The Ohio State
  University
• Jet Propulsion Laboratory
• Wallops Flight Facility
• Remote Sensing Solutions
• Electroscience Laboratory, The Ohio State
  University
• University of Iowa
• Concept Overview
• February 6, 2009

Imaging Greenland and Antarctica as they would
appear stripped of their icy cover
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Ice Sheet Mass Balance and Sea Level

• Ice sheet mass balance is described
• by the mass continuity equation

Altimeters
Act/Pass. Microwave
Obtaining ice thickness data around the perimeter
of the ice sheets remains a primary goal of the
ice sheet science community (ISMASS)
InSAR
Evaluations of the left and right hand sides of
the equation will yield a far more complete
estimate of the current contribution of ice
sheets to sea level rise. Moreover, unique, 3-d
imagery of the base will substantially improve
ice dynamics modeling enabling better predictions
of the future response of ice sheets to global
climate change
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Science Requirements

• 2 m vertical ice sheet surface height accuracy
  across the radar swath
• 10 cm vertical ice sheet surface height accuracy
  along laser scan for radar calibration and
  comparison with ICEsat
• 20 m vertical ice sheet base height accuracy for
  all ice covered terrain
• 20 m vertical accuracy on radar internal layers
  for ice dynamics
• 25 m geolocation accuracy (WGS 84/polar
  stereographic projections)
• Relative radiometric accuracy sufficient to
  discriminate basal rock from basal water
• 50 m pixels
• Continuous coverage with 100 km swath from
  grounding lines for both Greenland and
  Antarctica.
• Capability for 5-10 year repeat of integrated
  measurements for mapping redistribution of
  subglacial water (post Ventures addition to
  baseline measurement of topography)
• Data products to be integrable with DESDynI
  surface velocities and ICEsat surface topography

1st UHF image of ice sheet surface
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Team Organization
PI (Ken Jezek)
Product validation modeling (K. Jezek)
Operations Management (TBD)
Project management (TBD)
Science team Ernesto Rodriguez -
interferometry William Krabill - Surface
elevation change David Holland - ocean-ice sheet
modeling Christina Hulbe - numerical ice sheet
modeling Richard Hindmarsh - ice dynamics
modeling Joel Johnson radar scattering modeling
System operations (RSS)
Aircraft management (RSS)
Payload system engineering (G. Sadowy)
Product development (X. Wu, A. Safaeinili, J.
Sonntag)
WISE (A. Safaeinili)
GISMO (X. Wu)
LIDAR (B. Krabill)
Product distribution (Byrd, OSU)
Radar (B. Heavy, JPL) VHF Antennae (Volakis
Chen, OSU) Low Frequency Antenna (Kurth,
Kirchner, Iowa) Digital subsystem
(Carswell,Moller, RSS)
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Measurement Concept

• Three systems working together
• GISMO (Glaciers and Ice Sheet Mapping
  Observatory) radar (150-450 MHz) to map both
  surface and bottom of 3D topography of ice sheets
• WISE (JPL radar 1 20 MHz) to provide nadir
  depth sounding measurements of ice thickness for
  warmer and fractured ice
• WFF Lidar to provide accurate surface profile for
  elevation change detection to complement ICEsat
  and to provide validation for WISE and GISMO

Lidar
GISMO antenna hook up
GISMO
GISMO antenna hook up
Lidar antenna hook up
WISE antenna hook up
WISE
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Payloads WISE, GISMO, LIDAR
Airborne Topographic Mapper
Basal topography sensed using multi-antenna
tomographic SAR measurements at 150 MHz. New
antenna and receiver systems to Extend
GISMO 20 MHz bandwidth to 100 MHz Reduce
horizon gain of GISMO antenna to eliminate
late time surface clutter
WISE radar (demo version)
full-scale EM simulation
OSU miniature planar UWB antenna element
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Radar System Block Diagram
GISMO transmit antenna array

• Leverages GISMO and WISE designs
• Integrates both systems with a common controller
  and data system
• Also provides synchronization timing for WFF
  lidar system
• Full digital signal processing on both transmit
  and receive
• Three waveform generators
• Twenty digital receivers
• Real-time processing for data volume reduction
• All solid-state transmitters
• Design based on JPLs WISE radar and Europa
  Sounder with negligible risk to build

Transmitter
WISE antennae
Receiver
GISMO receive antenna array
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RSS Digital Receiver Data Acquisition

• RSS Team Brings
• Remote Sensing Systems Experience Developing
  end to end solutions for airborne remote sensing
  from manned and unmanned aircraft since 1990.
• Broad Experience 20 yrs in developing data
  acquisition management, embedded systems,
• radar digital receiver processing,
  processor and real-time operational data system
  solutions.
• FPGA-based Digital Receivers Developing state
  of the art, high performance, multi-channel
• airborne FPGA digital receiver solutions
  since 1998 for manned and unmanned platforms.
• Full Demonstration Developing Environment
  Hardware and software development boards
• and software to mitigate risk.

• Leverage RSS Receiver and Data System Technology
• - Multi-channel Digital Receiver Can support
  BIIR requirements.
• - Novel System Architecture Supports up to 16
  receiver channels,
• 25 Gb/s processing bus and 10 Gb/s
  CompactPCIe bus 3rd party support.
• - Embedded Network Processor Provides multiple
  independent Gigabit
• Ethernet interfaces for real-time access
  to data system and a means for
• efficient data distribution on ground.
• Utilize AAMPS Framework Novel network-based,
  remote access, real-time
• data acquisition, control, distribution
  visualization system developed for
• NOAA research aircraft.

Conduction Cooled 3U PCIe System
Virtex-5 Multi Channel Digital Receiver
Embedded Network Processor
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• Obtain 3-dimensional imagery of ice sheet surface
  and base by increasing level of complexity
• Phase 1 10 selected glacier basins in Greenland
  and Antarctica
• Phase 2 100 km strip from grounding line
• Post Ventures complete coverage
• Logistical requirement
• 5 hours per glacier system (500 km/hour, 10km
  swath)
• 1300 hours to cover 100 km strip about Antarctica
  from the grounding line
• 400 hours to cover 100 km strip about Greenland
• Conservative data collection cost estimate lt20
  M for phase 1 and 2 with 100 overhead and
  assuming 5K/flight hour

Operational Objectives
selected glaciers major aircraft stations
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Platform options Operating Concept

• Platform options
• Use available planes for early phase
• Ken Borek Air Twin Otter
  or NASA Wallops P-3 for
  Greenland
• Twin Otter or Air National Guard C-130 for
  Antarctica
• Wallops encourage BIIR use of P-3
• Unsolicited proposing that NSF recommission one
  of their Hercules C-130 planes for later phase.
• UAV possible but unlikely because of altitude and
  operational complexity
• Cycle GISMO, ATM, and WISE to avoid interference
  from simultaneous operation
• Fly over target area and collect return signals
  at on-board Operations Center
• Ocean flight calibration.
• Validation using existing data sets and cross
  flights.
• Real time on-board processing, on-field
  processing and post processing.

DAC January 2009
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Final Product Deliverables to Science Community

• Ice thickness maps
• Surface/base topography/intensity maps
• Bed rock/water classification maps
• Multilook azimuth compressed images
• Basal layer roughness and correlation length maps
• Internal layer images
• Google earth interface to final products, flight
  lines
• and raw data
  sets

Surface intensity map
3D base topography and intensity
Base image mosaic
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Multi-frequency images of ice sheet surface
across Jacobshavn glacier
Lake
Crevasse Band
Ice stream
24 km
7/20/2008, 150 MHz GISMO
Nov/Dec 2000, C-band Radarsat
7/15/08, MERIS optical image
17 km
July 20, 2008, 17 km wide, 150 MHz radar
tomography GISMO image (geocoded) of the upper
surface of the ice sheet across Jacobshavn
Glacier (right). 2000 Radarsat C-band image
(center). Inset map from Radarsat mosaic (left).
July 15, 2008, MERIS optical image (lower left).
GISMO image located at about 69.3N, 48.3 W
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Data processing scheme
WISE raw data
LIDAR raw data
GISMO raw data
Range compression
Multi-squint sounder processor
LIDAR processor
Calibration
GISMO processor
WISE processor
Data fusion processor
Beam Steering surface clutter rejection
Ice thickness data Surface topography/intensity
archive Base topography/intensity archive

• Tomography/interferometry processor
• Left - right separation
• Topography estimation
• Amplitude estimation

Orthorectification Image mosaic
Bed rock/water classifier
Processing time requirements can be met by
commercially available, low cost (lt100K),
multiprocessor architectures
Ice thickness maps Surface/base
topography/intensity maps Bed rock/water
classification maps
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Products and Information Flow
Final product archive Ice thickness maps
Surface topo/intensity maps Base topo/intensity
maps Water/rock classification maps Multilook
azimuth compressed images Basal layer roughness
and correlation length maps
Internal layer images Google earth interface
to final products, flight lines and
raw data sets
(20 GB)
Intermediate products (not archived) Range
compressed data Single look azimuth compressed
data
Raw data Archive (380 TB)
General public
Science community

• Only raw data and final products are archived.
• Raw data will be available to science community
  per request.
• Intermediate products including range compressed
  data and single look azimuth compressed data are
  not archived. But they will be available after
  reprocessing to science community per request.

• Conservative estimate of storage disk cost
  500K.
• Data distribution heritage from Radarsat
  Antarctic Mapping Mission http//bprc.osu.edu/rsl
  /radarsat/data/

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Summary

• The measurement is one-time shot due to the slow
  change of the bedrock elevation. It will stand as
  a reference climatological baseline.
• The technology is mature and proven. Radar system
  build is low risk (commercial or existing parts)
  and leverages JPL heritage.
• Unique ice thickness measurement directly
  complement DESDynI and ICESAT observation of
  surface velocity and surface elevation change
• Issues to be resolved during proposal phase
• Installation of antennas (e.g. NYANG 109th
  airforce flight worthiness restrictions)
• Logistical capabilities around Antarctica
• Instrument integration
• Supplement instruments (gravimeters)
• Potential Partners
• ESA has expressed possible interest in co-funding
  deployments as well as providing additional
  radar now supporting BIOMASS related experiments
• OPP/NSF C-130 logistics in Antarctica (e.g. fuel)
• Costs Conservative estimate of costs in order
  of 30M