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Three-dimensional passive source localization using a deep-water vector sensor vertical line array: A particle

Jianing Zhang^1,2,3, Erzheng Fang^1,2,3, Shiyu Gong^1,2,3

¹National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China.

The Journal of the Acoustical Society of America

|March 19, 2026

Summary

This summary is machine-generated.

This study introduces a track-before-detect (TBD) algorithm for improved 3-D passive localization of underwater sources using vector sensor vertical line arrays (VSVLAs). The method enhances detection accuracy in complex scenarios, reducing missed targets and measurement-to-track association issues.

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Published on: October 31, 2011

Area of Science:

Acoustics
Signal Processing
Oceanography

Background:

Passive localization of submerged sources in deep water typically uses vector sensor vertical line arrays (VSVLAs).
Shallow source localization involves two steps: 2-D spatial spectrum estimation (2DSSE) for azimuth/range and frequency matching for depth.
Multitarget scenarios with VSVLAs suffer from limited spatial resolution, leading to missed detections and measurement-to-track association (MTA) problems.

Purpose of the Study:

To develop an improved passive localization algorithm for submerged sources in complex deep-water environments.
To overcome limitations of traditional methods, specifically missed detections and MTA issues in multitarget scenarios.
To enhance the robustness and accuracy of three-dimensional (3-D) source localization.

Main Methods:

Implementation of a track-before-detect (TBD) framework to circumvent explicit MTA processing.
Joint scanning of intensity over an azimuth-range-depth grid using an interference-matched kernel function as input for TBD.
Integration of an auxiliary particle filter with adaptive weight filtering and Rao-Blackwellization for improved tracking performance.

Main Results:

The proposed TBD algorithm effectively mitigates missed detections caused by 2DSSE bright spot overlap.
The algorithm demonstrates high robustness under low signal-to-noise ratio (SNR) conditions and environmental fluctuations.
Simulations in complex deep-water scenarios and a towed-source experiment validate the localization performance.

Conclusions:

The TBD framework offers a superior approach to passive source localization in challenging underwater conditions.
The developed algorithm enhances detection capabilities and tracking accuracy compared to conventional methods.
The findings have significant implications for underwater surveillance and acoustic monitoring systems.