Spatiotemporal Analysis of Sonar Detection Range in Luzon Strait

Spatiotemporal Analysis of Sonar Detection Range in Luzon Strait

Gengming Zhang 1 , Lihua Zhang 1,*, YitaoWang 2,*, Yaowei Ma 1, Xingyu Zhou 1 and Yue Yu 3

1 Department of Military Oceanography and Hydrography, Dalian Naval Academy, Dalian 116000, China; zhanggengming1999@163.com (G.Z.); shhcube@163.com (Y.M.); 13805488150@163.com (X.Z.)

2 Software and Simulation Institute, Dalian Naval Academy, Dalian 116000, China

3 Unit 92538, Dalian 116000, China; 18640819235@163.com

* Correspondence: zlhua@163.com (L.Z.); wytbmdx@163.com (Y.W.)

Abstract: Sonar serves as a critical submarine detection apparatus for naval vessels, with its detection range forming the foundation of its overall performance in underwater surveillance. The Luzon Strait, in the eastern part of the South China Sea, presents a complex hydrographic setting that profoundly influences sonar performance, necessitating mastery of the detection range variation for enhanced anti-submarine operational efficiency. This study employs the Bellhop acoustic propagation model to estimate the transmission loss. 

Subsequently, a detection probability integration approach is applied to determine the sonar detection range in the Luzon Strait from 2019 to 2023, which is then subjected to statistical analysis. The findings indicate the following. 

(1) During the summer and autumn, the shallow mixed layer fails to generate a surface duct, resulting in shorter detection ranges that are primarily dependent on the water depth. In the Shallow Water Zone (<150 m), frequent interactions between sound waves and the sea boundaries lead to considerable acoustic energy attenuation, maintaining a short detection range. In the Intermediate Depth Zone (150–2500 m), sound rays retain adequate energy post-seabed reflection, extending the sonar detection to 5–8 km. Beyond 2500 m, the diminishing reflective energy restricts the range to 2–5 km. 

(2) Conversely, in the winter and spring, the formation of a surface duct becomes the predominant determinant of the detection range, capable of exceeding 10 km, overshadowing the influence of the water depth.

Keywords: Luzon Strait; sonar detection range; Bellhop acoustic propagation model; mixed layer depth

Summary

At the primary Naval Academy of the Chinese PLA Navy, researchers are studying sonar performance in a key area around the Phillipines. Here is a summary of the key points from the research article:

- The study analyzed sonar detection range (DR) variations in the Luzon Strait from 2019-2023 using the Bellhop acoustic propagation model.

- Key findings:
1. In summer/autumn, the shallow mixed layer results in shorter DRs mainly dependent on water depth:
   - Shallow water (<150m): Short DR (1-2km) due to energy loss from frequent reflections
   - Intermediate depths (150-2500m): DR of 5-8km
   - Deep water (>2500m): DR of 2-5km

2. In winter/spring, the thick mixed layer forms a surface sound channel, becoming the main factor influencing DR:
   - DRs are generally larger, exceeding 10km in some areas

- The mixed layer depth (MLD) and water depth were identified as the two primary factors affecting DR variations.

- An empirical formula was developed to predict DR using only MLD and water depth data, showing good agreement with simulated results.

- The study provides insights into spatiotemporal DR patterns in the Luzon Strait, which has implications for submarine detection and search operations in this strategically important area.

- Future work could focus on developing more advanced predictive models and applying the findings to optimize search path planning.

Bellhop Model

The Bellhop model is an acoustic propagation model used in underwater acoustics to simulate sound transmission in the ocean. Based on the information provided in the paper, here are some key points about the Bellhop model:

1. Methodology: It uses a Gaussian beam-tracing method to calculate acoustic propagation and transmission loss in the ocean.

2. Input requirements: The model requires input of the ocean's sound speed field to perform ray tracing and compute transmission loss.

3. Frequency range: Bellhop is effective for calculating acoustic fields within a frequency range of 0.6 to 30 kHz.

4. Accuracy: The model demonstrates excellent agreement with experimental data within its operational frequency range.

5. Recognition: It has been designated as the standard model for predicting ocean acoustic propagation within the frequency band of 10 to 100 kHz by the United States Navy.

6. Application in this study: The researchers used Bellhop to calculate the transmission loss, which is a crucial component in predicting sonar performance.

7. Mathematical basis: The paper provides some mathematical details of the Bellhop model, including equations for acoustic pressure field, beam width, and curvature.

8. Versatility: While not explicitly stated in this paper, Bellhop is known for its ability to handle range-dependent environments, making it suitable for complex oceanic conditions like those found in the Luzon Strait.

The Bellhop model's ability to accurately simulate acoustic propagation in various ocean environments makes it a valuable tool for studies like this one, which aim to understand and predict sonar detection ranges in complex marine settings. 

Data Sources

Based on the information provided in the paper, the following data sources were used in the study:

1. Temperature and salinity data:
   - Source: Hybrid Coordinate Ocean Model (HYCOM)
   - Availability: The data is openly available at https://tds.hycom.org/thredds/catalogs/GLBy0.08/expt_93.0.htm
   - The paper states this was accessed on 1 April 2024 (which is a future date, likely an error in the paper)

2. Bathymetric data:
   - Source: ETOPO 2022 (a global bathymetry and topography dataset)
   - Availability: The data is openly available at https://www.ncei.noaa.gov/products/etopo-global-relief-model
   - The paper states this was accessed on 1 April 2024 (again, likely an error in the date)

The paper does not mention any specific artifacts or databases created by the authors being made available. The results and analysis presented in the paper appear to be derived from these publicly available datasets using the Bellhop acoustic propagation model and the authors' own calculations and statistical analyses.

The paper does include an acknowledgment of these data sources: "This study acknowledges the provision of temperature and salinity data by HYCOM and bathymetric data by the U.S. National Geophysical Data Center."

If you're interested in replicating or building upon this study, you would likely need to access these public datasets and implement the Bellhop model and analysis methods described in the paper.