Improved Approximation of Sensor Network Performance for Seabed Acoustic Sensors

Sensor locations to detect Poisson-distributed targets, such as seabed sensors that detect shipping traffic, can be selected to maximize the so-called void probability, which is the probability of detecting all targets. Because evaluation of void probability is computationally expensive, we propose a new approximation of void probability that can greatly reduce the computational cost of selecting locations for a network of sensors. We build upon prior work that approximates void probability using Jensen’s inequality. Our new approach better accommodates uncertainty in the (Poisson) target model and yields a sharper error bound. The proposed method is evaluated using historical ship traffic data from the Hampton Roads Channel, Virginia, demonstrating a reduction in the approximation error compared to the previous approach. The results validate the effectiveness of the improved approximation for maritime surveillance applications.

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Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/oceans58557.2025.11184367
Citations
1
Primary Topic
Underwater Acoustics Research
Type
article
Field-Weighted Citation Impact
1.79
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article

Improved Approximation of Sensor Network Performance for Seabed Acoustic Sensors

Jorge Jimenez, Mingyu Kim, Daniel J. Stilwell, Harun Yetkin
1 citations
Underwater Acoustics Research
1.79
article

Improved Approximation of Sensor Network Performance for Seabed Acoustic Sensors

Jorge Jimenez, Mingyu Kim, Daniel J. Stilwell, Harun Yetkin
article en
1 citations

Abstract

Sensor locations to detect Poisson-distributed targets, such as seabed sensors that detect shipping traffic, can be selected to maximize the so-called void probability, which is the probability of detecting all targets. Because evaluation of void probability is computationally expensive, we propose a new approximation of void probability that can greatly reduce the computational cost of selecting locations for a network of sensors. We build upon prior work that approximates void probability using Jensen’s inequality. Our new approach better accommodates uncertainty in the (Poisson) target model and yields a sharper error bound. The proposed method is evaluated using historical ship traffic data from the Hampton Roads Channel, Virginia, demonstrating a reduction in the approximation error compared to the previous approach. The results validate the effectiveness of the improved approximation for maritime surveillance applications.

Johns Hopkins University Applied Physics Laboratory (US), Virginia Tech (US)
Openalex Percentile: Top 13%
Underwater Acoustics Research
1.79
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