Advanced signal processing methods for pulsed laser vibrometry

Abstract

Although pulsed coherent laser radar vibrometry has been introduced as an improvement over its Continuous Wave (CW) counterpart, it remains very sensitive to decorrelation noises such as speckle, and other disturbances of the measurement. Taking advantage of more polyvalent poly-pulse waveforms, we address the issue with advanced signal processing. We have conducted what we believe is the first extensive comparison of processing techniques considering CW, pulse-pair and poly-pulse emissions. In this framework, we introduce a computationally efficient maximum likelihood estimator and test signal tracking on pseudo time-frequency representations, which respectively help deal with speckle noise and fading of the signal, in harsh noise conditions. Our comparison on simulated signals is validated on a 1.55µm all-fiber vibrometer experiment, with an apparatus simulating vibration and strong speckle noise. Results show the advantage of estimators taking into account actual noise statistics, and call for a wider use of timefrequency representations to track the vibration modulated signal. OCIS codes: 280.0280, 280.3340, 120.7280. 2

Statistical model for fading return signals in coherent lidars

“…For any aperture diameter, the value of γ 0 is proportional to D 2 . As is expected when speckle is not considered [1], if D is less than r 0 , the mean SNR γ increases as the square of the diameter. When diameter D is larger than r 0 , atmospheric turbulence limits the effective receiving aperture to the dimensions of the coherence diameter r 0 .…”

“…During the past few decades, coherent lidar has established itself as a unique instrument in atmospheric remote sensing and its application area has broadened considerably (see, e.g., [1][2][3][4][5][6][7][8][9][10]) along with the technologies contributing to it [11]. Coherent lidars are currently employed in a large variety of atmospheric applications in fields as diverse as laser vibrometry and target identification [1,2], meteorological observation and atmospheric wind determination [3,4], aerosol and atmospheric constituent concentration measurements [5][6][7], and tracking and control of pollutants atmospheric fluxes [8][9][10].…”

“…Coherent lidars are currently employed in a large variety of atmospheric applications in fields as diverse as laser vibrometry and target identification [1,2], meteorological observation and atmospheric wind determination [3,4], aerosol and atmospheric constituent concentration measurements [5][6][7], and tracking and control of pollutants atmospheric fluxes [8][9][10].…”

Methods for the quantification of pseudo-vibration sensitivities in laser vibrometry

“…The amplitude and phase of the photodetector output therefore result from a phasor summation with implications for signal amplitude and measurement noise. Any particular phasor summation can result in an inadequate photodetector signal amplitude, known as 'dropout', and this is a longstanding challenge [2,3] that remains of current interest both in LDV [4] and in related, emerging techniques [5,6]. During set-up, this problem may be remedied by minor adjustment of the position of the incident laser beam, but during measurements, even very small surface motions can induce sufficient changes in the sampled speckle pattern to cause dropouts which appear as spikes in the instrument output.…”

Compensation for the Decoherence Effect in Heterodyne Detection of Rough Targets and a Target Vibration Characteristic Measurement System

“…Besides system parameters, the performance of a coherent detection system heavily depends on the characteristics of a target surface. In a coherent laser detection system, the return signal from a diffuse scattering surface are subject to the effects of phase fluctuation (the 'decoherence effect' [17][18][19], which can severely degrade heterodyne system performance [20][21][22][23][24][25] .…”