2017
DOI: 10.3390/s17061315
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Joint Estimation of Source Range and Depth Using a Bottom-Deployed Vertical Line Array in Deep Water

Abstract: This paper presents a joint estimation method of source range and depth using a bottom-deployed vertical line array (VLA). The method utilizes the information on the arrival angle of direct (D) path in space domain and the interference characteristic of D and surface-reflected (SR) paths in frequency domain. The former is related to a ray tracing technique to backpropagate the rays and produces an ambiguity surface of source range. The latter utilizes Lloyd’s mirror principle to obtain an ambiguity surface of … Show more

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Cited by 17 publications
(4 citation statements)
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“…A simple two-path ray model that only takes into account the direct contribution and the sea surface reflected gives quite accurate approximations, even in deep water [ 15 ]. As illustrated in Figure 6 , the SAMARUC PAM system (green dot) is placed at depth and the source at depth .…”
Section: Methodsmentioning
confidence: 99%
“…A simple two-path ray model that only takes into account the direct contribution and the sea surface reflected gives quite accurate approximations, even in deep water [ 15 ]. As illustrated in Figure 6 , the SAMARUC PAM system (green dot) is placed at depth and the source at depth .…”
Section: Methodsmentioning
confidence: 99%
“…Their team estimated the target depth by analyzing the number of fringes [18] and made improvements to handle the situation of low signal-to-noise ratio (SNR) and weak source depth fluctuations [19]. Some scholars mapped the sound field to other domains based on the interference structure of the sound field to achieve effective separation of source depth [20,21].…”
Section: Introductionmentioning
confidence: 99%
“…For broadband targets, the interference pattern in the frequency domain is also applicable to underwater source localisation [6]. Li et al [7] presented a joint-source range and depth estimation method using a bottom-deployed scalar VLA. In recent years, the method of machine learning has aroused great heat [8,9].…”
Section: Introductionmentioning
confidence: 99%
“…Li et al. [7] presented a joint‐source range and depth estimation method using a bottom‐deployed scalar VLA. In recent years, the method of machine learning has aroused great heat [8, 9].…”
Section: Introductionmentioning
confidence: 99%