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Path: Imaging/Optics
% Detector model with photon and electron noise sources and A/D conversion.
Includes all noise sources. You enter target or centroid locations.
You can define centroids using e.r, e.theta and e.h for shape. If you
enter a pixelmap, it is assumed to be in photons - it is multiplied by the
quantum efficiency to get the electron counts.
You must call DetectorModel( 'initialize', e ) first and then p =
DetectorModel( 'update', e, p, i ) on every update step. The fixed noise
parameters are stored in persistent cariables,
Since version 11.
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Form:
e = DetectorModel( 'struct' )
DetectorModel( 'initialize', e )
p = DetectorModel( 'update', e, p, i )
[r,m] = DetectorModel( 'rss', e )
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Inputs
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e (.) Data structure
.m (1,1) Rows
.n (1,1) Columns
.f (1,1) Focal length (mm)
.a (1,1) Aperture (mm)
.pixel (1,1) Pixel dimension (micro-m)
.tau (1,1) Integration time (s)
.qE (1,1) Quantum efficiency (e-/photon)
.eta (1,1) Throughput
.lambda (1,1) Wavelength (nm)
.r (1,1) Distance from sun (AU)
.kappa (1,1) Stray light multiplier
.fpn (1,1) Fixed pattern noise (e-)
.ndr (1,1) Temporal noise (e-)
.dark (1,1) Dark current (e-/s)
.alpha (1,1) Global photo response non uniformity
.kTC (1,1) Temperature noise (e-)
.kAD (1,1) A/D conversion (V/e-)
.gain (1,1) A/D gain Forward A/D gain
.bits (1,1) A/D bits
.vS (1,1) Voltage swing (V)
.centroid (1,1) Flag is true for centroid locations
.rho (1,n) Centroid radial value (pixel)
.theta (1,m) Angle about the centroid
.h (1,n) Normalized height at radial position
x (2,:) Position in pixel plane (m) or pixel map
i (:,1) Intensity (photons/s)
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Outputs
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p (n,m) Pixels (V)
r (1,1) Root sum square of the noise (e-) or
m (1,1) Mean noise (e-)
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Reference: M. Knutson and D. Miller, "Fast Star Tracker Centroid
Algorithm for High Performance CubeSat with Air Bearing
Validation," June 2012 MIT SSL # 5-12
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See also:
Centroids, ZodiacalLight
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Imaging: Optics/Centroids Imaging: Optics/FocalPlaneImage Imaging: Optics/RMSNoiseImager Imaging: Optics/ZodiacalLight Math: Probability/RandPN
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