Laser bulk damage thresholds were measured for both single-crystal YAG and for diffusion-bonded YAG structures
using 600 picosecond pulses at 1064 nm. The tested samples included 3-layer sandwich structures with doped cores
of various thicknesses. An undoped-YAG end cap was diffusion-bonded on one end of each of the sandwiches. The
1064 nm laser source was focused to a 13 micron diameter spot at the boundary region between the core and the
undoped endcap. Measurements included the evaluation of single- and multiple-pulse damage thresholds at single
sites, as well as thresholds for continuous 90%-overlap scans. The single-site thresholds at the diffusion-bonded
boundary were close to that of single-crystal YAG. However, the continuous scans revealed isolated microscopic
sites where the damage threshold was as much as 4 times lower than that of single-crystal YAG.
Several lidar campaigns have been performed in support of calibration/validation of DMSP SSM/T-2 microwave water vapor sensors. Calibration capabilities were demonstrated by performing radiative transfer calculations based on water vapor profiles measured by lidar. The calculations agreed with collocated SSM/T-2 atmospheric channel measurements to better than 1K RMS, whereas discrepancies were frequently greater than 2 K for radiative transfer based on conventional AIR and Vaisala radiosonde profiles. The improved capability is attributed to the new ability to measure water vapor from 8 to 14 km altitude. Conventional radiosondes tend to be unresponsive to water vapor at the low temperatures typical of altitudes above 8 km.
KEYWORDS: Data modeling, Doppler effect, Vibrometry, Laser processing, Signal processing, Statistical signal processing, Stochastic processes, Spectrum analysis, Data processing, Fermium
Laser vibration sensing provides a sensitive non-contact means of measuring vibrations of objects. These measurements are used in industrial quality control and wear monitoring as well as the analysis of the vibrational characteristics of objects. In laser vibrometry, the surface motion is monitored by heterodyne laser Doppler velocimetry, and the received heterodyne signal is sampled to produce a time-series which is processed to obtain a vibrational spectrum of the object under test. Laser vibrometry data has been processed with a traditional FM discriminator approach and by spectrogram and time-frequency distribution processing techniques. The latter techniques have demonstrated improved performance over the FM discriminator method, but do not take full advantage of the prior knowledge one has about the signal of interest. We consider here a statistical signal processing approach to laser vibrometry data. In this approach the quantities of interest are the frequencies of vibration, while the phase and quadrature amplitudes are considered nuisance parameters. Because of the optimal use of prior knowledge about the laser vibrometry signal, the frequencies can be determined with much greater precision and greater noise immunity than using Fourier- or time-frequency-based approaches. Furthermore, the statistical approach is known to have superior performance when the data extends over a small number of vibrational periods. We illustrate the method with data from a fiber-optic laser Doppler velocimeter. Our results show that while the choice of processing method for determining the instantaneous velocity is relatively unimportant, the Bayesian method exhibits superior performance in determining the vibrational frequency.
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