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• W1930759849 abstract "Acoustic signals in a shallow ocean environment are severely distorted due to the time-varying and inhomogeneous nature of the propagation channel. In this paper, a state-space model is introduced to characterize the uncertainties of the shallow ocean and a Rao-Blackwellized particle filter (RBPF) is developed to estimate the model parameters. Since both modal functions and horizontal wave numbers of the channel are assumed unknown, the state-space model has a high nonlinearity and high dimensionality. As the modal functions are linear with the measurements conditioning on the horizontal wave numbers, a Kalman filtering (KF) is employed to marginalize out the modal functions. Hence only the horizontal wave numbers need to be estimated by using a PF. Simulation results show that the proposed RBPF algorithm significantly outperforms the existing approaches." @default.
• W1930759849 created "2016-06-24" @default.
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• W1930759849 date "2015-09-01" @default.
• W1930759849 modified "2023-09-22" @default.
• W1930759849 title "Particle filtering for channel parameter tracking in a noisy shallow ocean environment using a vertical array" @default.
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• W1930759849 doi "https://doi.org/10.1109/apsar.2015.7306246" @default.
• W1930759849 hasPublicationYear "2015" @default.
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