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Characterization of modulated time-of-flight range image sensors
Author(s) -
Andrew D. Payne,
Adrian A. Dorrington,
Michael J. Cree,
Dale A. Carnegie
Publication year - 2008
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.806007
Subject(s) - image sensor , pixel , duty cycle , frequency modulation , envelope (radar) , computer science , modulation (music) , waveform , range (aeronautics) , optics , phase modulation , time of flight , sampling (signal processing) , computer vision , artificial intelligence , acoustics , physics , engineering , radio frequency , radar , telecommunications , voltage , phase noise , quantum mechanics , filter (signal processing) , aerospace engineering
A number of full field image sensors have been developed that are capable of simultaneously measuring intensity and distance (range) for every pixel in a given scene using an indirect time-of-flight measurement technique. A light source is intensity modulated at a frequency between 10–100 MHz, and an image sensor is modulated at the same frequency, synchronously sampling light reflected from objects in the scene (homodyne detection). The time of flight is manifested as a phase shift in the illumination modulation envelope, which can be determined from the sampled data simultaneously for each pixel in the scene. This paper presents a method of characterizing the high frequency modulation response of these image sensors, using a pico-second laser pulser. The characterization results allow the optimal operating parameters, such as the modulation frequency, to be identified in order to maximize the range measurement precision for a given sensor. A number of potential sources of error exist when using these sensors, including deficiencies in the modulation waveform shape, duty cycle, or phase, resulting in contamination of the resultant range data. From the characterization data these parameters can be identified and compensated for by modifying the sensor hardware or through post processing of the acquired range measurements

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