Volume 133, Issue 4, April 2013
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
133(2013); http://dx.doi.org/10.1121/1.4794370View Description Hide Description
In this paper, the task of model-based transmit signal design for optimizing detection is considered. Building on past work that designs the spectral magnitude for optimizing detection, two methods for synthesizing minimum duration signals with this spectral magnitude are developed. The methods are applied to the design of signals that are optimal for detecting elastic objects in the presence of additive noise and self-noise. Elastic objects are modeled as linear time-invariant systems with known impulse responses, while additive noise (e.g., ocean noise or receiver noise) and acoustic self-noise (e.g., reverberation or clutter) are modeled as stationary Gaussian random processes with known power spectral densities. The first approach finds the waveform that preserves the optimal spectral magnitude while achieving the minimum temporal duration. The second approach yields a finite-length time-domain sequence by maximizing temporal energy concentration, subject to the constraint that the spectral magnitude is close (in a least-squares sense) to the optimal spectral magnitude. The two approaches are then connected analytically, showing the former is a limiting case of the latter. Simulation examples that illustrate the theory are accompanied by discussions that address practical applicability and how one might satisfy the need for target and environmental models in the real-world.
133(2013); http://dx.doi.org/10.1121/1.4792151View Description Hide Description
Uncorrelated scattering (US), which assumes that multipath arrivals undergo uncorrelated scattering and are thus uncorrelated, has been the standard model for digital communications including underwater acoustic communications. This paper examines the cross-correlation of multipath arrivals based on at-sea data with different temporal coherence time, assuming quasi-stationary statistics. It is found that multipath arrivals are highly cross-correlated when the channel is temporally coherent, and are uncorrelated when the channel is temporally incoherent. A theoretical model based on the path phase rates and relative-phase fluctuations is used to explain experimentally observed phenomena, assuming the path amplitudes vary slowly compared with the phases. The implications of correlated scattering for underwater acoustic communication channel tracking are discussed.
133(2013); http://dx.doi.org/10.1121/1.4792247View Description Hide Description
Acoustic channel estimation is an important problem in various applications. Unlike many existing channel estimation techniques that need known probe or training signals, this paper develops a blind multipath channel identification algorithm. The proposed approach is based on the single-input multiple-output model and exploits the sparse multichannel structure. Three sparse representation algorithms, namely, matching pursuit, orthogonal matching pursuit, and basis pursuit, are applied to the blind sparse identification problem. Compared with the classical least squares approach to blind multichannel estimation, the proposed scheme does not require that the channel order be exactly determined and it is robust to channel order selection. Moreover, the ill-conditioning induced by the large delay spread is overcome by the sparse constraint. Simulation results for deconvolution of both underwater and room acoustic channels confirm the effectiveness of the proposed approach.
133(2013); http://dx.doi.org/10.1121/1.4792359View Description Hide Description
This paper presents an application of the data completion method (DCM) for vector intensity reconstructions. A mobile array of 36 pressure-pressure probes (72 microphones) is used to perform measurements near a planar surface. Nevertheless, since the proposed method is based on integral formulations, DCM can be applied with any kind of geometry. This method requires the knowledge of Cauchy data (pressure and velocity) on a part of the boundary of an empty domain in order to evaluate pressure and velocity on the remaining part of the boundary. Intensity vectors are calculated in the interior domain surrounded by the measurement array. This inverse acoustic problem requires the use of a regularization method to obtain a realistic solution. An experiment in a closed wooden car trunk mock-up excited by a shaker and two loudspeakers is presented. In this case, where the volume of the mock-up is small (0.61 ), standing-waves and fluid structure interactions appear and show that DCM is a powerful tool to identify sources in a confined space.