Target Localization for a Distributed SIMO Sonar With an Isogradient Sound Speed Profile

He, Chaofeng; Wang, Yiyin; Chen, Cailian; Guan, Xinping

doi:10.1109/access.2018.2843438

Cited by 13 publications

(13 citation statements)

References 28 publications

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“…Different from the situation of our previous work [4], there are uncertainties in the locations of the receivers. In order to reduce the influence of the uncertainties on the target localization, we estimate the clock skews of the receivers in conjunction with the locations of the receivers with EM algorithm.…”

Section: The Utls Algorithmmentioning

confidence: 63%

“…Both of them are assumed to be known as a priori. For a single ray such as the ray from the target to the receiver normalri as shown in Figure 1, the time-of-flight (ToF) [4] τi can be expressed in an explicit form w.r.t. x and boldxiτi≜fifalse(boldx,xifalse)=1aln[adi+a2di2+4cfalse(zifalse)cfalse(zfalse)]24c(zi)c(z),i=1,2,⋯,M,h,where di=false(xi−xfalse)2+false(yi−yfalse)2+false(zi−…”

Section: System Modelsmentioning

confidence: 99%

“…As shown in Table 1, the competitors include the NWLS-UTL algorithm, the WLS-NWLS algorithm, the AWLS-NWLS algorithm, the ANWLS algorithm, and the NWLS-RP algorithm. The NWLS-UTL algorithm is proposed in [4] for underwater target localization. In our proposed UTLS algorithm, the NWLS algorithm is employed to estimate the location of the target with the values of the clock skews and clock offsets estimated by the EM and WLS algorithms, respectively.…”

Section: Numerical Simulationsmentioning

confidence: 99%

“…Multistatic sonar can provide superior localization accuracy and detection performance as well as improved robustness and flexibility over its monostatic counterpart [1]. There are several typical multistatic systems enabling target localization, such as multi-input multiple-output (MIMO) sonar/radar [2,3], single-input multiple-output (SIMO) sonar/radar [4,5], wireless sensor networks [6] and multistatic radar [7,8]. Multiple trials conducted by the Centre for Maritime Research and Experimentation [9] have shown that multistatic sonar systems can provide better detection, localization and tracking performances than monostatic sonars.…”

Section: Introductionmentioning

confidence: 99%

“…however, the time synchronization is ignored by them. A target localization algorithm is proposed for a distributed SIMO sonar with an isogradient SSP in our previous work [4]. A delay model is presented in an explicit form with respect to (w.r.t.)…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations

Wang

et al. 2019

Sensors

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A distributed single-input multiple-output (SIMO) sonar system is composed of a sound source and multiple underwater receivers. It provides an important framework for underwater target localization. However, underwater hostile environments bring more challenges for underwater target localization than terrestrial target localization, such as the difficulties of synchronizing all the underwater receiver clocks, the varying underwater sound speed and the uncertainties of the locations of the underwater receivers. In this paper, we take the sound speed variation, the time synchronization and the uncertainties of the receiver locations into account, and propose the underwater target localization and synchronization (UTLS) algorithm for the distributed SIMO sonar system. In the distributed SIMO sonar system, the receivers are organized in a star topology, where the information fusion is carried out in the central receiver (CR). All the receivers are not synchronized and their positions are known with uncertainties. Moreover, the underwater sound speed is approximately modeled by a depth-dependent sound speed profile (SSP). We evaluate our proposed UTLS algorithm by comparing it with several benchmark algorithms via numerical simulations. The simulation results reveal the superiority of our proposed UTLS algorithm.

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Section: The Utls Algorithmmentioning

confidence: 63%

Section: System Modelsmentioning

confidence: 99%

Section: Numerical Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations

Wang

et al. 2019

Sensors

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Underwater angle-only tracking with propagation delay and time-offset between observers

Ali

2020

Signal Processing

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Enhancement of Precise Underwater Object Localization

Sathish

Anbazhagan

et al. 2023

Radio Science

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Underwater communication applications extensively use localization services for object identification. Because of their significant impact on ocean exploration and monitoring, underwater wireless sensor networks (UWSN) are becoming increasingly popular, and acoustic communications have largely overtaken radio frequency (RF) broadcasts as the dominant means of communication. The two localization methods that are most frequently employed are those that estimate the angle of arrival (AOA) and the time difference of arrival (TDoA). The military and civilian sectors rely heavily on UWSN for object identification in the underwater environment. As a result, there is a need in UWSN for an accurate localization technique that accounts for dynamic nature of the underwater environment. Time and position data are the two key parameters to accurately define the position of an object. Moreover, due to climate change there is now a need to constrain energy consumption by UWSN to limit carbon emission to meet net‐zero target by 2050. To meet these challenges, we have developed an efficient localization algorithm for determining an object position based on the angle and distance of arrival of beacon signals. We have considered the factors like sensor nodes not being in time sync with each other and the fact that the speed of sound varies in water. Our simulation results show that the proposed approach can achieve great localization accuracy while accounting for temporal synchronization inaccuracies. When compared to existing localization approaches, the mean estimation error (MEE) and energy consumption figures, the proposed approach outperforms them. The MEEs is shown to vary between 84.2154m and 93.8275m for four trials, 61.2256m and 92.7956m for eight trials, and 42.6584m and 119.5228m for twelve trials. Comparatively, the distance‐based measurements show higher accuracy than the angle‐based measurements.This article is protected by copyright. All rights reserved.

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Target Localization for a Distributed SIMO Sonar With an Isogradient Sound Speed Profile

Cited by 13 publications

References 28 publications

Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations

Underwater Target Localization and Synchronization for a Distributed SIMO Sonar with an Isogradient SSP and Uncertainties in Receiver Locations

Underwater angle-only tracking with propagation delay and time-offset between observers

Enhancement of Precise Underwater Object Localization

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