A study on the array gain estimation using an AIS-based shipping noise model

Title
A study on the array gain estimation using an AIS-based shipping noise model
Author(s)
박지성; 강돈혁; 조성호
KIOST Author(s)
Kang, Don Hyug(강돈혁)Cho, Sung Ho(조성호)
Alternative Author(s)
박지성; 강돈혁; 조성호
Publication Year
2018-06-05
Abstract
Array gain (AG) occurs when sensors are arranged in an array, and is generally calculated as the ratio of the signal-to-noise ratio (SNR) between the array and a single sensor. The AG is a metric to measure the performance of the array. When a plane wave signal is received from a single direction and is perfectly coherent, and when the ambient noise around the array is isotropic, the AG is equal to the directivity index (DI). However, the AG can be changed in the presence of directional noise. In this case, the AG can be calculated from the directional noise using the spatial coherence. The major cause of marine background noise in the low-frequency (<1 kHz) band is the radiated noise from ships in coastal areas and harbors. If the directional noise of the ships can be estimated, the AG of the array can be predicted.
In this study, the AG is calculated based on the spatial coherence between the array elements using the directionality of shipping noise that is derived by using the ship-tracking data and navigational information of automatic identification system (AIS). A power-law model was applied to estimate the source level (SL) of the ship based on its length and speed obtained via the AIS, and the received level (RL) of the noise according to the azimuth angle was derived by applying the sonar equation (RL = SL - TL). The transmission loss (TL) was calculated using a range-dependent acoustic model (RAM). The predicted AG based on the spatial coherence is then compared with the AG measured through the sea-going experiment. The result was confirmed that the AG prediction using the AIS-based shipping noise modeling will be effectively used to evaluate the performance of the array (This research was funded by KIOST (PE99643, PG49550))
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23246
Bibliographic Citation
2nd Oceanoise Asia Symposium, pp.54, 2018
Publisher
2nd OCEANOISE ASIA
Type
Conference
Language
English
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