Robust localization using geographic information in bistatic sonar

Lee, Kwang Hee; Jeong, Eun Jeong; Kim, Seong‐Il; Han, Dong Seog

doi:10.1177/1550147717714172

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…Wettergren () considers the problem of detecting moving targets over large areas using a network of fixed sensor nodes and proposes the track‐before‐detect concept, which accounts for tracking information and multisensor data fusion. Lee, Jeong, Kim, and Han () propose a robust localization algorithm for bistatic sonar sensors that accounts for errors in the source position, receiver position, and sound speed. They use simulation to compare the performance of the algorithm with the conventional localization algorithms.…”

Section: Related Workmentioning

confidence: 99%

Bistatic sonobuoy deployment strategies for detecting stationary and mobile underwater targets

Karataş

Craparo

Akman

2018

Naval Research Logistics

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The problem of determining effective allocation schemes of underwater sensors for surveillance, search, detection, and tracking purposes is a fundamental research area in military operations research. Among the various sensor types, multistatic sonobuoy systems are a promising development in submerged target detection systems. These systems consist of sources (active sensors) and receivers (passive sensors), which need not be collocated. A multistatic sonobuoy system consisting of a single source and receiver is called a bistatic system. The sensing zone of this fundamental system is defined by Cassini ovals. The unique properties and unusual geometrical profile of these ovals distinguish the bistatic sensor allocation problem from conventional sonar placement problems. This study is aimed at supporting decision makers in making the best use of bistatic sonobuoys to detect stationary and mobile targets transiting through an area of interest. We use integral geometry and geometric probability concepts to derive analytic expressions for the optimal source and receiver separation distances to maximize the detection probability of a submerged target. We corroborate our analytic results using Monte Carlo simulation. Our approach constitutes a valuable "back of the envelope" method for the important and difficult problem of analyzing bistatic sonar performance.

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Section: Related Workmentioning

confidence: 99%

Bistatic sonobuoy deployment strategies for detecting stationary and mobile underwater targets

Karataş

Craparo

Akman

2018

Naval Research Logistics

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“…As another type of underwater target localization, underwater source localization is also a hotspot [27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43]. The authors of [27] implement source localization from the sparse signal reconstruction perspective.…”

Section: Introductionmentioning

confidence: 99%

“…Some works take the location uncertainties of the anchors into consideration [31,32,33,34,35,36,37,38] in source localization. The authors of [31,32,33] analyse the effect of anchor location errors on source localization.…”

Section: Introductionmentioning

confidence: 99%

“…The synchronization clock bias and sensor position errors are considered in the TDOA source localization in [37]. In [38] a robust localization algorithm using geographic information in bistatic sonar is proposed for source localization. Some researchers attempt to find a close-form solution for underwater source localization [39,40,41,42,43].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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Localisation for underwater acoustic networks with a piece-wise linear sound speed profile

Wang,

Ding,

Shang

et al. 2024

Ships and Offshore Structures

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Robust localization using geographic information in bistatic sonar

Cited by 3 publications

References 18 publications

Bistatic sonobuoy deployment strategies for detecting stationary and mobile underwater targets

Bistatic sonobuoy deployment strategies for detecting stationary and mobile underwater targets

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

Localisation for underwater acoustic networks with a piece-wise linear sound speed profile

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