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Infant Auditory Processing and Event-related Brain Oscillations

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Difference frequency coherent matched autoproduct processing for source localization in deep ocean.

Ze Yuan¹, Haiqiang Niu¹, Zhenglin Li²

¹State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, People's Republic of China.

The Journal of the Acoustical Society of America

|April 24, 2023

Summary

This summary is machine-generated.

Coherent matched autoproduct processing (CMAP) enhances passive source localization by improving spatial resolution and sidelobe suppression. This advanced technique offers more robust and accurate underwater acoustic detection compared to traditional methods.

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Area of Science:

Underwater Acoustics
Signal Processing
Array Signal Processing

Background:

Matched autoproduct processing (MAP) is a passive source localization technique using frequency-difference autoproducts.
MAP offers environmental mismatch insensitivity but suffers from low spatial resolution and poor peak-to-sidelobe ratio.
Conventional matched field processing (MFP) and incoherent MAP have limitations in passive source localization accuracy.

Purpose of the Study:

To improve spatial resolution and peak-to-sidelobe ratio in passive source localization.
To introduce and validate coherent approaches, specifically coherent matched autoproduct processing (CMAP).
To assess the performance of CMAP and its phase-only variant against conventional methods.

Main Methods:

Extended coherent normalized MFP to develop coherent matched autoproduct processing (CMAP).
CMAP exploits correlations among autoproducts at various difference frequencies.
Phase-only CMAP utilizes only phase information for passive source localization.

Main Results:

Simulations in Munk sound-speed profile and South China Sea environments demonstrated CMAP's effectiveness.
CMAP and phase-only CMAP significantly suppressed sidelobes and enhanced localization resolution and robustness.
Experimental measurements validated the simulation findings, showing improved performance over MFP and incoherent MAP.

Conclusions:

Difference frequency coherent algorithms, like CMAP, offer superior performance for passive source localization.
CMAP effectively addresses the limitations of conventional MAP and MFP in terms of resolution and sidelobe levels.
The developed coherent techniques provide a more robust and accurate solution for underwater passive acoustic detection.