A novel hyperspectral imager based on microslice technology A novel hyperspectral imager based on...
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A novel hyperspectral imager based on microslice technology
Ray Sharples, Danny Donoghue, Robert ContentColin Dunlop, David Nandi, Gordon Talbot
Durham University
UAV Workshop7th July 2011
Outline of Presentation
• Background• Methods for simultaneous 3D
spectroscopy• Operating principles of a microslice
hyperspectral imager• First laboratory results from a CEOI-
funded prototype sensor• Future Plans
Project Background
Telescopefocus
Spectrographinput
Lensletarray
Fibrearray
Imageslicer
1 2 3 4
Both designs maximise the spectrum length and allows more efficient utilisation of detector surface.
Only the image slicer retains spatial information within each slice/sample high information density
in datacube
Overlaps must be avoided less information density in datacube
Spectrographoutput
slitFibres
Pupilimagery
slit1
2
3
4
Micro-mirrors
x
y
Datacube
Divides the field in two dimensions
• Fully exploit modern large-format 2D detectors to obtain faster survey speeds.
• Longer exposures in stare-mode to allow higher SNR in finer pixels for radiometry, meteorology & and atmospheric composition studies - particularly important for low reflectivity targets such as water, forestry and shallow marine environments.
• Enable smaller, more compact devices than other comparable platforms. Compact designs using state-of-the-art sensors to reduce mass/volume requirements.
• Step-change in the imagery available to assist in meeting NERC targets for Earth observation with applications in many areas: not in the least vegetation, geology and pollution monitoring.
• CEOI Seedcorn Project: budget £50k.
A New Approach to Hyperspectral
Imaging
V km/sec
x
Dwell time = x/V
Instrument Layout
CEOI Mid-Term Review Meeting 12 Jan 2011
Pick-off mirror Collimator
Image slicer
Fore-optics
GRISM
Camera
Baseplate
(cover omitted)
Dimensions 33 cm x 15 cm x 12 cmMass ~5 kg (excl baseplate)
Hyperspectral Imaging Using Microslice Technologies
• Novel application of microlens resampling optics to deliver unprecedented field-of-view sampling over multiple spectral channels simultaneously.
• Addresses current spectral resolution and sensitivity limitations with available airborne/spaceborne instruments.
• Enables high spectral resolution observations to characterise and quantify ecosystem and land/water surface properties.
• Allows spectral fingerprinting to be scaled up to address whole Earth system processes.
Prototype Microslice Spectrograph
• NERC Centre for Earth Observation Instrumentation Seedcorn Project started April 2010.
• 330 x 20 “spaxels” (spatial pixels each giving a spectrum) so 6,600 spectra.
• Spectra 180 pixels long
• Resolution of 5-7 nm (slice images 3 pixel wide) over 400 nm to 700nm
• Dimensions 33 cm x 15 cm x 12 cm
Application Tests
• Lab set up Microslicer & ASD FieldSpec Pro• Objectives:
– Test spectral resolution– Test signal / noise ratio– Ability to extract spectra– Use Spectralon standard
Advantages of Microslice Hyperspectral Imagers
• Rapid survey speeds with options for multiple viewing geometries.
• High spatial resolution with no limitations due to scanning speed on a single overpass as with pushbroom techniques.
• High spectral and spatial resolutions.
• Longer exposures in stare-mode to allow higher SNR in finer pixels for radiometry, meteorology and atmospheric composition studies.
• Signal strength is also particularly important for low reflectivity targets such as water and shallow marine environments.
• Compact design using state-of-the-art sensors to reduce mass/volume requirements.
Summary
• Knowledge transfer from astronomy to remote sensing is opening up new concepts for hyperspectral imaging of the environment.
• Extreme multiplex microslice technologies offer a new approach to obtain high spatial and spectral resolution simultaneously over a 2D FoV.
• The use of step and stare modes offer the potential for 2-3 orders of magnitude increase in S/N compared with pushbroom or whiskbroom approaches and also allows monitoring of time-dependent processes.
Further Details:Prof. Ray Sharples - [email protected]. Danny Donoghue - [email protected]