Abstract-This paper presents a stochastic model of a turbulent shallow-water acoustic channel. The model utilizes a Monte Carlo realization method to predict signal transmission conditions. The main output from the model are statistical descriptions of the signal-to-multipath ratio (SMR) and signal fading. Probability density functions of signal envelope are evaluated by Pearsons's Skew-Kurtosis Chart, generally predicting Ricean fading. Dynamic calculations of SMR by the model overcome the main inconveniences of deterministic calculations, providing "smooth" instead of "noisy" curves as a result. Dynamic calculations of SMR and fading are concluded to provide more intelligible and realistic results than deterministic calculations.
Fluctuations in the scattering of high-frequency sound from the moving sea surface is of significance, particularly in underwater acoustic communication systems using adaptive methods. Surface scattering may statistically be described using coherence functions, especially for higher frequencies when the coherent part of the pressure field is virtually nonexistent. Previous studies have presented coherence functions as a function of either spatial and temporal variations of the channel, but with a fixed signal carrier frequency or two signal frequencies and temporal channel variations (or some of the several possible Fourier transform duals). Here, a coupled bispectral, temporal and spatial coherence function is presented. The coherence function is derived from the pressure field, given by the two-dimensional Kirchhoff–Helmholtz integral for two monochromatic tones evaluated at separate receiver positions. The channel variations are caused by a wind-driven, gravity-wave dispersed sea surface with a Pierson–Moskowitz spectrum. The derivation of the coherence function involves numerical integration. Numerical results are compared to earlier model data from the literature. [Work sponsored by the Danish Technical Research Council.]
High-level spontaneous otoacoustic emissions (SOAEs) were measured from 16 ears using both spectral and time averaging. The purpose was to determine the source of an upward shift in frequencies of synchronized SOAEs (SSOAEs) observed while using a subroutine of the ILO88 system of Otodynamics Ltd. An HP3561A signal analyzer performed spectral averaging to extract SOAEs with no external stimulation applied to the ear canal. Synchronized SOAEs were derived using the ILO88 system performing time averaging following click stimulation. The frequencies of all SSOAEs were shifted upwards by 6 to 21 Hz when compared to corresponding SOAE frequencies determined with spectral averaging. Additional measurements of signals in a cavity and of click-evoked otoacoustic emissions in selected ears indicated that the frequency shift is the result of an error in the ILO88 software. Incorrect cursor readouts in the program cause an apparent upward shift in frequency of 12.2 Hz. This error was confirmed by the manufacturer.Spontaneous otoacoustic emissions ͑SOAEs͒ represent narrow-band signals that can be recorded in the outer ear canal when no external acoustic stimulation is presented ͑see Probst et al., 1991 for a review͒. In general, two methods have been used to record them. In the first, the sound-pressure level in the ear canal is measured by a low-noise microphone with no stimulation applied. The microphone signal is averaged in the frequency domain ͑e.g., Whitehead et al., 1993͒. The second method consists of recording SOAEs synchronized by acoustic stimuli, for example clicks, using averaging in the time domain. This enables the detection of long lasting oscillations following click-evoked otoacoustic emissions ͑CEOAEs͒. It has been shown that for an ear with strong SOAEs, a CEOAE spectrum exhibits peaks corresponding to SOAE frequencies ͑Probst et al., 1986; Gobsch and Tietze, 1993͒. Software of a widely used commercially available instrument for measuring OAEs, the ILO88 ͑Otodynamics Ltd., Hatfield, UK͒, includes a subroutine for measuring synchronized spontaneous otoacoustic emissions ͑SSOAEs͒. Several recent studies have reported SSOAE data collected with the ILO88 system ͑Wable and Collet, 1994; Kulawiec and Orlando, 1995; Prieve and Falter, 1995͒. As part of an ongoing study of otoacoustic emissions in normal-hearing humans in our laboratory, we have measured SOAEs using both spectral averaging and the synchronization technique of the ILO88. In comparing the two results from the same ear, we have observed a slight but consistent difference in the frequencies of SSOAEs and SOAEs. Therefore, we sought to characterize this discrepancy further and to determine its source. Because of the widespread use of the ILO system, we believe that it is important that our findings be reported.Both ears of eight subjects from our laboratory pool who had known SOAEs that were at least 10 dB above the noise floor of the instrumentation were tested with two methods. In the first method, the sound-pressure level in the ear canal was me...
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