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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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Staring Imaging Overview
Gazing at the Solar System: Capturing the Evolu8on of Dunes, Faults, Volcanoes and Ice from Space
KISS Workshop 2014
Joseph Green
Jet Propulsion Laboratory California Ins8tute of Technology
June 16, 2014
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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Canonical Remote Sensing Telescopes
§ Pushbroom Imagers
– Images scene with a linear array of pixels • Mul8ple rows opera8ng in a TDI mode
– Satellite ground track sweep forms 2nd dimension of image • Low Earth Orbit (400-‐1000 km) • Ground Track moves at 7 km/s
– Implemented with Several Linear FPAs (panchroma8c, mutl8spectral)
• MISR – 9 Different 4-‐band (VNIR) cameras at different viewing angles • LANDSAT – 7 Bands (VNIR, MWIR and TIR) • ASTER – 15 bands (VIS, SWIR and TIR) • WORLDVIEW 2 – 8 Bands (Pan + MSI: 400-‐1000nm)
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
3
Canonical Remote Sensing Telescopes
§ Design Space for Pushbroom Imagers – Very limited integra.on .me due to projected orbital velocity (7km/s)
– Systems are undersampled to minimize line-‐of-‐sight blur and to benefit FOV • Q=1.00 for panchroma8c imaging (1 sample per resolu8on element) • Q=0.25 for mul8spectral imaging (To maintain same integra8on 8me as Pan) • Q=2.00 would be cri8cally sampled (2 samples per resolu8on element)
– Larger telescope diameter (and/or lower al.tude) is needed to make up resolu8on loss due to low-‐Q
– Op8mized for world mapping applica8ons with area-‐rate-‐coverage being a driver • Tend to collect single (to few) observa.ons of a target in a pass • May take many orbits for a subsequent revisit
Q = λ*fn / Pixel Pitch
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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Key Problem in Classic Remote Sensing
§ Orthorec?fica?on – High Precision Orthorec8fica8on is required to related images between difference
observa8on 8mes and different sensors – Problem difficulty driven by disparity in viewing geometry against high relief targets – Further complexity from changes in scene contents between revisists – When done well, it enables mosaicing, change detec8on and data fusion processes
AFIDS (Automa?c Fusion of Image Data System)
Landsat-‐7 Image, 2002
Landsat-‐5 Orthorec?fied Mosaic ~1990
Nevin A. Bryant, Thomas L. Logan, Albert L. Zobrist, “Precision Automa?c Co-‐Registra?on Procedures for SpacecraU Sensors”, Paper 6550 published in the ASPRS Annual Mee?ng Proceedings, Denver, CO, May 27, 2004
Example Courtesy of : Nevin Bryant, JPL
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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LEO Orbit Example
Contours shown for 30 and 45 degree Target ElevaEon Angles from 900km
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Staring Imagers § Fixed-‐Point-‐Stare Imaging
– Vehicle rotates to maintain a fixed aim point to the ROI during pass • Cancels out principal ground mo8on
– Images are acquired with a a 2-‐D Focal Plane Array
– Examples • Skybox!! • Weather Satellites • Cameras on the ISS
Houston at Night from ISS Taken by Donald R. Pettit, JSC
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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Staring Imagers § Design Space for Staring Imagers
– Long Integra.on .mes possible (up to 1000msec) before residual orbital blur is
an issue • Primary ground track mo8on is canceled • Secondary dynamic effects of from scene scale and rota8on are slow
– System can be well-‐sampled (Q = 1.5-‐2.0) while maintaining a good imaging SNR • Both Pan and MSI modes can be well sampled • Integra.on .me is free to be a variable • Not constrained to operate at high sun-‐eleva.on angles
– Telescope diameter (and al.tude) can be co-‐op8mized with relaxed Q • Leads to smaller telescopes flying higher to achieve the same resolu8on
– Op8mized for persistence and con8nuous angle diversity • Collec8ons can have 100’s to 1000’s of frames
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Fixed-‐Point-‐Staring Applica?ons
§ Enables New Processing Capabili?es – Automa8c change detec8on, tracking and flow-‐measurements – 3D Visualiza8on (e.g. Anaglyphs – but with highly tunable disparity) – 3D Reconstruc8on – Sun/Viewing Angle induced effects (e.g. BRDF es8ma8on) – Mul8frame super-‐resolu8on – High Dynamic Range Imaging
• Exploit range of integra8on 8mes to overcome finite FPA Dynamic Range
§ Automa8on of pass-‐ensemble data is straight forward
.94 ms
127.3 ms
3.97 ms
7.95 ms
15.97 ms
31.94 ms
63.89ms
1.95 ms
Example: High Dynamic Range Imaging HDRI Study Lead: Sidd Bikannavar, JPL
• Eight 12-‐bit exposures synthesize 21-‐bit image • Gradient-‐domain tonal mapping methods used to display image
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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Example Scenario § Simula8on of star8ng imaging from low Earth orbit
– Ground target (47.0132° N, 122.9241° W) – Satellite al8tude = 900 km
§ Imaging system – Panchroma8c channel – Aperture diameter = 1 m – Ground sample distance = 0.5 m – Time between images = 1 min – Comparable to high-‐resolu8on commercial imager (WorldView-‐1)
Simulations and Subsequent 3D Results by Sam Thurman (formerly of JPL)
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
10 STT – 10
Joint Es?ma?on of Scene and Pose Scene Radiance
Scene Eleva?on [meters]
Satellite Ephemeris
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§ Higher Orbits enable more time on target
§ ~50x longer range results in dramatically lower resolution images
§ Need large space telescope for resolution!!
Non-LEO Orbits
500km (perigee)
Molniya (12-hour) 42000km (apogee)
Geosynchronous (24-hour) 36000km
GOES-West Example Courtesy of Mike Burl, JPL
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GEO Seismic Imager (Previous KISS Study) PI: David Redding, JPL
March 13, 2012
§ An ISS-assembled 6m telescope for imaging large earthquakes
§ Telescope is pointed in response to events detected on the ground
§ Stationed in GEO over the Pacific coast of the Americas, GSI would be in position to observe 1 to 4 Mv > 6 earthquakes per year
§ GSI data would revolutionize earthquake seismology
0
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40 6_7
7_7.5
7.5_8
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1999
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Magnitudes 5 to 6
Mag
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Mission Start Date
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Num
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Numbers of Viewable Earthquakes vs. Mission Start Date
Red = daytime Black = night
Barrel Secondary Mirror (SM) SM Hexapod Support Structure 18 Segment Primary Mirror (PM) PM Segment Support Structure Instrument Camera Suites (ICS) Payload Electronic Box x 4 Space X Dragon Lab SC Bus
Notional GSI launch packaging in 8 Dragon Lab trunks (9th provides bus)
For 10 year missions
For 10 year missions
Scene cm
0 km 8km 16km 8 km 16km 8km 16km
True dy
The
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at
Calif
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a Sh
akeo
ut
Estimated dy Simulation of GSI Imaging and Data Processing
• Image frame rate is 2Hz, with 20 min of rolling data storage • Resolution as good as 1 cm on a 200m grid, over a field of view up
to 300 km by 300 km • Surface deformation movies reveal rupture propagation, enabling
correlation of ground motion to subsurface geology • GSI data could ultimately lead to effective warning capabilities and
to improved public management of earthquake risk
A 6 m GSI assembled at the ISS
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Remarks § Staring Imagers provide a unique opera?onal and design space for
telescopes – Long integra8on 8mes – Large ensemble SNR per pass – High level of of con8nuous angular diversity – High-‐Q maximizes ‘processibility’ of data
§ Must be matched to the right science applica?on – Target focused (not world mapping centric)
Nothing in this world can take the place of persistence. Talent will not: nothing is more common than unsuccessful men with talent.
Genius will not; unrewarded genius is almost a proverb. Education will not: the world is full of educated derelicts. Persistence and
determination alone are omnipotent.
- Calvin Coolidge
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National Aeronautics and Space Administration!Jet Propulsion Laboratory!California Institute of Technology!
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Backup
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Pushbroom vs Staring
Pushbroom Imaging Staring Imaging Integra?on Time 0.1 -‐ 3 msec (TDI) Up to 1000 msecs
Orbital Constraints Sun-‐synchronous (10AM-‐2PM) Highly relaxed Focal Plane Technology 1-‐D Linear Arrays (TDI) 2-‐D Focal Plane Arrays
Mul?spectral Implementa?on Mul8ple Linear Arrays w/filters Filter Wheel, Dichroics, Bayer-‐Filter…
Imaging Q 0.25 -‐ 1.0+ (Op8mized for Int Time) Up to 2.0 (Op8mized for Resolu8on) Aperture Diameter Large to overcome low-‐Q Significantly Smaller (Matched to Q)
Frames per Pass 1 to 10's 100's to 1000's Field of View Large (Array + Sweep Limited) Small (FPA limited)
Targets per Orbit Many 10's 2 -‐ 10 Persistence on Target very limited 4-‐10 minutes
Data Quality Issues 2D image not rigid (sweep/LOS errors) Time-‐separa8on between bands
Aliasing in Imagery from low-‐Q 'Grain' in images from high-‐Q