Publications
Estimating Acoustic Mode Functions of a Deep Water Waveguide Using Ambient Noise Measurements
Abstract
Assuming that the signals recorded by a vertical line array (VLA) consist of a sum of uncorrelated modes, the modeshapes can be determined from an eigenvector decomposition of the measured cross spectral density matrix. Several authors have applied this technique to estimate the modes of shallow water waveguides. Wolf et al. estimated the modes of an 18 m deep waveguide using data from an array spanning the entire water column [Proceedings of the 1993 IEEE Oceans Conference, vol. I, pp. 99-104]. Hursky et al. explored the problem of using data-derived modeshapes and wavenumbers for matched field processing in the SWellEx-96 experiment [J. Acoust. Soc. Am., 109(4), pp. 1355-1366]. Nielsen and Westwood estimated modeshapes for the Hudson Canyon environment using both CW towed sources and ambient noise [J. Acoust. Soc. Am., 111(2), pp. 748- 756]. While the general approach pursued by these authors should work for deep water environments, very few experiments have deployed VLA's with long enough aperture to resolve the modes propagating in a deep water waveguide. In previous work D'Spain et al. computed numerical estimates of modes from earthquake T-phase arrivals on a 3000 m VLA [Pure appl. geophys., Vol. 158, pp. 475-512]. In this work we focus on estimating the modeshapes for a deep water environment in the North Pacific using ambient noise data measured during the SPICE04 experiment. The SPICE04 VLA had 40 hydrophones spanning 1400 m and centered around the sound channel axis. Although noise measurements were not the primary focus of SPICE04, the experiment provided a large data set for this noise analysis. In addition to acoustic measurements, the SPICE04 experiment also included extensive sampling of temperature and salinity. This talk summarizes the noise statistics measured during 2004-2005 and compares the empirical modes derived from the data with the true modes derived from the measured environmental data.
[Work supported by an ONR Young Investigator Award.]
This talk was presented at the 2007 Underwater Acoustic Signal Processing Workshop (UASP) , sponsored by the IEEE Providence Section in cooperation with the IEEE Signal Processing Society. The abstract may be found on the UASP website.