Presentation on theme: "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."— Presentation transcript:
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
Outline Gas detection and Emitter detection Technique Description Derivation of Theoretical Responsivity Description of the Experiment Theoretical Vs. Experimental Results Conclusion
Gas detection Broadband Light source Intervening Gas Cloud Sensitive Optical detection system Spectrum
Coherence Length The coherence length of a light source is given by where is the path difference in the interferometer
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.
Theory 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. F.T. Path Difference (microns) Detector Reading (mV)
Gaussian Model Gaussian spectrum target Rectangular filtered background spectrum Normalised self coherence function of both is given by
Gaussian Model Notation is the path difference is the filtered background optical bandwidth is the target optical bandwidth PR is the target to background power ratio after filtering erf is the error function 0 is the central wavenumber of the target and filter passbands, assumed coincident.
Gaussian Modelling The first null occurs when N = 0 This can be solved graphically
Graphical solution to N = 0
Differential Detection Responsivity The amount the null is displaced when the power ratio of the target to background is increased.
Differential Detection Responsivity N is the path difference position of the null N is the amount that is moves when the power ratio is increased by PR Maximum detection responsivity occurs when bandwidth ratio, ( ) = 0.262
Target/Filter Combinations Maximum detection responsivity occurred in the Gaussian theory when bandwidth ratio, ( ) = This lies between set 2 and 3.
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 , experiment used
Results - Wavelength Offset
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.
Conclusions The differential detection responsivity can be maximised by choosing the filter bandwidth to suit the target bandwidth ( ) = Design of filter transmission curve is another degree of freedom to be exploited to improve the differential detection responsivity
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.