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- W1979923811 abstract "In passive sonar systems, knowledge of low-frequency shipping noise is significant for target detection performance. However, an accurate model for the shipping noise structure is difficult to obtain, because of the varying distributions of ships and complicated underwater environment. This work characterizes low-frequency distant shipping noise observed in deep water environments as a function of receiver depth and vertical arrival structure placed below the conjugate depth. Distant shipping noise is examined using a Monte Carlo simulation based on statistics derived from the Historical Temporal Shipping (HITS) database. Source levels and source depths of ships are assigned depending on the ship classification. The complex pressure field radiated from each interferer is computed using a normal mode propagation model, and the predicted values are summed coherently at each receiver location. Parameters for the ocean channel are chosen in agreement with the experimental observations, and sensitivity to exact parameters of the bottom sediment is explored. The depth dependence of the simulated shipping noise is in agreement with published experimental measurements. A Vertical Line Array (VLA) is used to produce vertical beams that isolate the surface interference from nearby targets. Simulation results quantifying the beamformer output as a function of ocean environment, receiver aperture, and frequency are presented for both conventional and adaptive beamformers. The results suggest a favorable detection performance of a target in the presence of distant shipping interferers and wind noise, by adaptive beamforming using diagonal loading with white noise gain constraint techniques." @default.
- W1979923811 created "2016-06-24" @default.
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- W1979923811 date "2010-09-01" @default.
- W1979923811 modified "2023-10-16" @default.
- W1979923811 title "Vertical arrival structure of shipping noise in deep water channels" @default.
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- W1979923811 doi "https://doi.org/10.1109/oceans.2010.5664539" @default.
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