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.
Authors
- Jorge Jimenez (ORCID: https://orcid.org/0000-0002-0858-8115)
- Mingyu Kim (ORCID: https://orcid.org/0009-0009-1246-8456)
- Daniel J. Stilwell (ORCID: https://orcid.org/0000-0002-5410-2024)
- Harun Yetkin (ORCID: https://orcid.org/0000-0001-5611-9041)
Institutions
- Johns Hopkins University Applied Physics Laboratory (US)
- Virginia Tech (US)
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