Volume 128, Issue 1, July 2010
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
128(2010); http://dx.doi.org/10.1121/1.3425729View Description Hide Description
Acoustic localization is a promising method to passively observe vocal animal species, but remains difficult and time consuming to employ. To reduce the labor intensity and impact of deployment, an acoustic localization system has been developed consisting of battery powered wireless sensor nodes. The system also has the ability to perform an acoustic self-survey, which compares favorably in accuracy to global positioning system survey methods, especially in environments such as forest. The self-survey and localization accuracy of the system was tested in the neotropical rainforest of Chiapas, Mexico. A straight-forward and robust correlation sum localization computation method was utilized and is described in detail. Both free-ranging wild antbird songs and songs played from a speaker were localized with mean errors of 0.199 m and 0.445 m, respectively. Finally, additional tests utilizing only a short segment of each song or a subset of sensor nodes were performed and found to minimally affect localization accuracy. The use of a wireless sensor network for acoustic localization of animal vocalizations offers greater ease and flexibility of deployment than wired microphone arrays without sacrificing accuracy.
128(2010); http://dx.doi.org/10.1121/1.3436521View Description Hide Description
Detecting and locating changes in a waveguide can be extremely difficult. A method is suggested here which does not require simplification of the problem (no spherical chickens) nor any modeling of the waveguide nor of the propagation within it. The method relies only on previous broadband data recorded on an array of receivers (two or more) which is then compared to more recent data to investigate change. Backscatteredenergy is to be examined here although bistatic configurations may also be possible. This approach is applicable whenever there is sufficient, appropriate data for comparison (note that absolute levels are not needed) and can be applied to acoustically search for scatterers introduced to an ocean zone (such as targets or pollutants), blockages or changes in sewer pipes, or even to non-acoustic energy in a waveguide, e.g., the use of electromagnetic energy in the earth-ionosphere waveguide. This method is based on the signal processing technique known as matched field processing and will be demonstrated on a variety of laboratory sewer pipe data. The method (particularly for localization) is introduced here, as is the suggestion for application to general waveguide environments.
128(2010); http://dx.doi.org/10.1121/1.3392441View Description Hide Description
Methods of measuring the acoustic behavior of tubular systems can be broadly characterized as steady state measurements, where the measured signals are analyzed in terms of infinite duration sinusoids, and reflectometrymeasurements which exploit causality to separate the forward and backward going waves in a duct. This paper sets out a multiple microphonereflectometry technique which performs wave separation by using time domain convolution to track the forward and backward going waves in a cylindrical source tube. The current work uses two calibration runs (one for forward going waves and one for backward going waves) to measure the time domain transfer functions for each pair of microphones. These time domain transfer functions encode the time delay, frequency dependent losses and microphone gain ratios for travel between microphones. This approach is applied to the measurement of wave separation, bore profile and input impedance. The work differs from existing frequency domain methods in that it combines the information of multiple microphones within a time domain algorithm, and differs from existing time domain methods in its inclusion of the effect of losses and gain ratios in intermicrophone transfer functions.
Ship classification using nonlinear features of radiated sound: An approach based on empirical mode decomposition128(2010); http://dx.doi.org/10.1121/1.3436543View Description Hide Description
Classification for ship-radiated underwater sound is one of the most important and challenging subjects in underwater acoustical signal processing. An approach to ship classification is proposed in this work based on analysis of ship-radiated acoustical noise in subspaces of intrinsic mode functions attained via the ensemble empirical mode decomposition. It is shown that detection and acquisition of stable and reliable nonlinear features become practically feasible by nonlinear analysis of the time series of individual decomposed components, each of which is simple enough and well represents an oscillatory mode of ship dynamics. Surrogate and nonlinear predictability analysis are conducted to probe and measure the nonlinearity and regularity. The results of both methods, which verify each other, substantiate that ship-radiated noises contain components with deterministic nonlinear features well serving for efficient classification of ships. The approach perhaps opens an alternative avenue in the direction toward object classification and identification. It may also import a new view of signals as complex as ship-radiated sound.