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The innovation of touch-tone telephony revolutionized the telecommunications industry by replacing the traditional rotary dial with a dual-tone multi-frequency (DTMF) signaling system. This system uses a matrix-style keypad with buttons arranged in four rows and three columns, creating 12 distinct signals each assigned to a pair of frequencies. Each button press results in a simultaneous generation of two sinusoidal tones – one from a low-frequency group (697 to 941 Hz) and one from a...

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Michael D Collins¹, Ralph N Baer, Harry J Simpson

¹Naval Research Laboratory, Stennis Space Center, Mississippi 39529, USA. mike.collins@nrlssc.navy.mil

The Journal of the Acoustical Society of America

|September 8, 2011

Summary

This summary is machine-generated.

Acoustic source localization in noisy environments was tested. A noise-canceling processor accurately determined source range in challenging conditions, outperforming other methods.

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Area of Science:

Acoustics
Signal Processing
Ocean Engineering

Background:

Accurate localization of acoustic sources in noisy environments is crucial for various applications.
Matched-field processing (MFP) is a common technique, but performance degrades significantly in low signal-to-noise ratio (SNR) conditions.
Realistic experimental scenarios are needed to validate signal-processing techniques.

Purpose of the Study:

To evaluate the effectiveness of different signal-processing techniques for acoustic source localization in a noisy waveguide.
To compare the performance of a noise-canceling processor against Bartlett and multivalued Bartlett processors.
To assess localization accuracy under various noise conditions and signal-to-noise ratios.

Main Methods:

A tank experiment simulating a realistic underwater waveguide with water and sediment layers was conducted.
Acoustic noise was generated using a discrete source, bubble generator, and sprinkler.
Signal-processing algorithms, including Bartlett, multivalued Bartlett, and a noise-canceling processor, were applied to recorded time series data.

Main Results:

The noise-canceling processor demonstrated superior performance compared to the Bartlett processor.
The noise-canceling processor successfully provided correct source range localization for signal-to-noise ratios below -10 dB.
The multivalued Bartlett processor outperformed the standard Bartlett processor but did not match the noise-canceling processor's effectiveness.

Conclusions:

Noise-canceling processors offer a significant advantage for acoustic source localization in low SNR environments.
The experimental setup effectively replicated key challenges of realistic matched-field processing scenarios.
Further development of noise-robust signal-processing techniques is warranted for underwater acoustic applications.