Adaptive Range Optimization Using Henry Gas Solubility Optimization for Energy-Efficient Acoustic Pinger Detection in Shallow Coastal Waters

International Journal of Electrical and Electronics Engineering

© 2025 by SSRG - IJEEE Journal

Volume 12 Issue 10

Year of Publication : 2025

Authors : Afsar Ali, Kaja Mohideen, Vedachalam

10.14445/23488379/IJEEE-V12I10P105

How to Cite?

Afsar Ali, Kaja Mohideen, Vedachalam, "Adaptive Range Optimization Using Henry Gas Solubility Optimization for Energy-Efficient Acoustic Pinger Detection in Shallow Coastal Waters," SSRG International Journal of Electrical and Electronics Engineering, vol. 12,  no. 10, pp. 55-68, 2025. Crossref, https://doi.org/10.14445/23488379/IJEEE-V12I10P105

Abstract:

The challenge of detecting underwater acoustic pingers (e.g., aircraft blackboxes) in the shallow coastal waters is (1) due to the complex multipath propagation, (2) due to the variation of environmental conditions, and (3) due to the limited energy budgets. The techniques proposed in this paper to calibrate the sensing and communication limit of hydrophone nodes in a distributed underwater acoustic sensor network include using the Henry Gas Solubility Optimization (HGSO) technique. The technique uses the Ainslie framework to determine the Transmission Loss (TL) of a given place by taking into consideration the real-time environmental factors like depth, salinity, temperature, background noise, and pH. The HGSO aims to minimize energy consumption, maximize detection rate, minimize TL, and preserve network connection by employing a multi-objective fitness function. HGSO's performance is compared and contrasted with that of three state-of-the-art metaheuristic techniques, viz., Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). The simulation results show that HGSO gets the lowest TL of 84.3 dB at the best range of 2200 meters, and it converges in 60 iterations. On the other hand, PSO and GA give higher TLs of 86.7 dB and 87.9 dB at longer ranges (2450 m and 2600 m), but they need 85 and 95 iterations, respectively. GWO gets a TL of 85.2 dB, but it takes longer to converge, at 70 iterations. HGSO also exhibits the slightest convergence variance (±0.5 dB) and the highest detection probability (92%), indicating that it performs well even in unpredictable underwater conditions. Thus, HGSO is a reliable method for detecting black box signals in shallow and changing-depth water, making it particularly useful for search and rescue operations at sea.

Keywords:

Acoustic pinger detection, Energy-efficient sensing, Henry gas solubility optimization, Shallow water acoustics, Transmission loss modeling.

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