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Detection of weak optical signals

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The recorded interferogram is processed using a computer algorithm to extract a ... Discussion. In our model we assumed a Gaussian target spectrum. ... – PowerPoint PPT presentation

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Title: Detection of weak optical signals


1
Detection of weak optical signals
  • D.R. Selviah, R.C. Coutinho, H.A. French and H.D.
    Griffiths
  • Department of Electronic and Electrical
    Engineering,
  • University College London,
  • United Kingdom

2
Outline
  • Gas detection and Emitter detection
  • Technique Description
  • Derivation of Theoretical Responsivity
  • Description of the Experiment
  • Theoretical Vs. Experimental Results
  • Conclusion

3
Gas detection
Spectrum
Spectrum
Sensitive Optical detection system
Broadband Light source
Intervening Gas Cloud
4
Emission Target Detection
Spectrum
Spectrum
Sensitive Optical detection system
Broadband Light source
Weak Narrow linewidth emitter
5
Typical Unfiltered Interferogram, GN(t)
6
Coherence Length
  • The coherence length Dt of a light source is
    given by
  • where t is the path difference in the
    interferometer

7
Basics
  • Technique combining optical and digital signal
    processing to detect coherent or partially
    coherent sources in an incoherent environment
  • Employs an optical narrowband filter to generate
    a specific feature in the self coherence function
    measured with an interferometer
  • Unlike Fourier transform spectroscopy (FTS), the
    path difference is scanned in a tiny region
    surrounding the first minimum of the self
    coherence function (interferogram), thus
    achieving faster frame rates
  • The recorded interferogram is processed using a
    computer algorithm to extract a phase step in the
    fringe signal its position is used to declare
    detection.

8
Theory
Detector Reading (mV)
F.T.
Path Difference (microns)
  • If a spectrally narrow emission source enters the
    field of view, the net degree of coherence of the
    scene changes, shifting the position of the first
    minimum in the self coherence function (see next
    slide). This shift is measured and used for
    detection
  • The approach senses the change in the spectrum
    through measurements of the change in a region of
    the interferogram, which makes it a lot faster
    than other spectral approaches.

9
The signal
10
Phase Step Detection Algorithm
11
Gaussian Model
  • Gaussian spectrum target
  • Rectangular filtered background spectrum
  • Normalised self coherence function of both is
    given by

12
Gaussian Model Notation
  • t is the path difference
  • Dk is the filtered background optical bandwidth
  • d is the target optical bandwidth
  • PR is the target to background power ratio after
    filtering
  • erf is the error function
  • k0 is the central wavenumber of the target and
    filter passbands, assumed coincident.

13
Gaussian Modelling
  • The first null occurs when ?GN? 0
  • This can be solved graphically

14
Graphical solution to ?GN? 0
15
Differential Detection Responsivity
  • The amount the null is displaced when the power
    ratio of the target to background is increased.

16
Differential Detection Responsivity
  • tN is the path difference position of the null
  • ? tN is the amount that is moves when the power
    ratio is increased by ? PR
  • Maximum detection responsivity occurs when
    bandwidth ratio, (d/Dk) 0.262

17
Experimental Arrangement
18
Target/Filter Combinations
  • Maximum detection responsivity occurred in the
    Gaussian theory when bandwidth ratio, (d/Dk)
    0.262
  • This lies between set 2 and 3.

19
Results - Responsivity
20
Results - Responsivity
  • Theory and experiment have similar form with the
    experiment confirming the bandwidth ratio for the
    highest responsivity.
  • Discrepancy in the magnitude of theory and
    experiment.
  • Theory used a larger range of power ratios from 0
    - 1.11, experiment used 0.005 - 0.31

21
Results - Wavelength Offset
22
Discussion
  • In our model we assumed a Gaussian target
    spectrum.
  • Other line shapes for emission and absorption
    should be included in the theory.
  • We assumed a rectangular filter response.
  • More realistic filter responses should be
    included.

23
Conclusions
  • The differential detection responsivity can be
    maximised by choosing the filter bandwidth to
    suit the target bandwidth
  • (d/Dk) 0.262
  • Design of filter transmission curve is another
    degree of freedom to be exploited to improve the
    differential detection responsivity

24
Conclusions
  • Experimentally a coherent narrow linewidth
    source, a laser could be detected at about
    -44 dB below the broadband white light
    background.
  • Experimentally an LED about 40 nm linewidth
    source could be detected at about -33 dB below
    the broadband white light background.
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