The Sonar Simulation Toolset, Release 4.6: Science, Mathematics, and Algorithms

Goddard, Robert P.

doi:10.21236/ada487996

Cited by 27 publications

(27 citation statements)

References 34 publications

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“…In order to provide the best fidelity in simulating the ocean environment, the Sonar System Toolset (SST) was used to realistically model the acoustic environment. SST is an application developed by the University of Washington Applied Physics Laboratory [11] and provides a flexible architecture for conducting underwater acoustic simulations.…”

Section: Simulation Resultsmentioning

confidence: 99%

Directed subspace search ML-PDA with application to active sonar tracking

Blanding

Willett

Bar‐Shalom

et al. 2008

IEEE Trans. Aerosp. Electron. Syst.

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The Maximum Likelihood Probabilistic Data Association (ML-PDA) tracking algorithm is effective in tracking Very Low Observable targets (i.e., very low signal-to-noise ratio (SNR) targets in a high false alarm environment). However, the computational complexity associated with obtaining the track estimate in many cases has precluded its use in real-time scenarios. Previous ML-PDA implementations used a multi-pass grid search to find the track estimate. In this paper, two alternate methods for finding the track estimate are presented -a genetic search and a newly developed directed subspace (DSS) search algorithm. Each algorithm is tested using active sonar scenarios in which an autonomous underwater vehicle searches for and tracks a target. Within each scenario, the problem parameters are varied to illustrate the relative performance of each search technique. Both the DSS search and the genetic algorithm are shown to be an order of magnitude more computationally efficient than the multi-pass grid search, making possible real-time implementation. In addition, the DSS search is shown to be the most effective technique at tracking a target at the lowest SNR levels -reliable tracking down to 5 dB (post-processing SNR in a resolution cell) using a 5-frame sliding window is demonstrated, this being 6 dB better than the multi-pass grid search.

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Section: Simulation Resultsmentioning

confidence: 99%

Directed subspace search ML-PDA with application to active sonar tracking

Blanding

Willett

Bar‐Shalom

et al. 2008

IEEE Trans. Aerosp. Electron. Syst.

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“…Simulated element-level data generated by the Sonar Simulation Toolset (SST) [5] was used to assess the effectiveness of both cued beams and surveillance beams in a variety of scenarios. Specifically, the behavior of < ∆H > as a function of prior PDF width, diagonal loading level, and contact SNR was examined for both CBF and ABF.…”

Section: Resultsmentioning

confidence: 99%

“…The acoustic environment used for simulations was a 100 m deep isospeed ocean over a clayey-sand halfspace [5]. The contact sources radiated a steady tone with wavelength λ = 7.5 m (corresponding to a frequency of f = 200Hz in a water with a sound speed of 1500 m/s.)…”

Section: Simulation Detailsmentioning

confidence: 99%

Cued beamforming of passive arrays in the context of active-passive data fusion

Yudichak¹,

Yocom²,

Lê³

2007

Proceedings of Meetings on Acoustics

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“…[8] model type •: modeling approach is both applicable (physically) and practical (computationally) ◐: limitations in accuracy or in speed of execution ○: neither applicable nor practical. low frequency (<500 Hz), high frequency (>500 Hz) RI: range-independent environment RD: range-dependent environment [1,[9][10][11] 음선 기반의 음파 전달 알고리즘은 고전적인 음선 추적법과 가우시안 빔 추적법으로 나뉠 수 있다. [12][13][14] 고전적인 음선 추적법은 고주파수 근사 이론에 의해 …”

Section: 정영철 이근화 성우제 김형록unclassified

Development of Range-Dependent Ray Model for Sonar Simulator

Jung¹

2014

The Journal Of The Acoustical Society Of Korea

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Sound propagation algorithm for a sonar simulator is required to run in real-time and should be able to model the range and depth dependence of the Korean ocean environments. Ray model satisfies these requirements and we developed an algorithm for range-dependent ocean environments. In this algorithm, we considered depth-dependence of sound speed through rays based on a rectangular cell method and layer method. Range-dependence of sound speed was implemented based on a split-step method in the range direction. Eigen-ray is calculated through an interpolation of ray bundles and Gaussian interpolation function was used. The received time signal of sonar was simulated by Fourier transform of eigen-ray solution in the frequency domain. Finally, for the verification of proposed algorithm, we compared the results of transmission loss with other validated models such as BELLHOP, SNUPE, KRAKEN and OASES, for the Pekeris waveguide, wedge, and deep ocean environments. As a result, we obtained satisfactory agreements among them.

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The Sonar Simulation Toolset, Release 4.6: Science, Mathematics, and Algorithms

Cited by 27 publications

References 34 publications

Directed subspace search ML-PDA with application to active sonar tracking

Directed subspace search ML-PDA with application to active sonar tracking

Cued beamforming of passive arrays in the context of active-passive data fusion

Development of Range-Dependent Ray Model for Sonar Simulator

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