Portland State University. Department of Electrical and Computer Engineering
Lisa M. Zurk
Date of Publication
Master of Science (M.S.) in Electrical and Computer Engineering
Electrical and Computer Engineering
Beamforming, Underwater acoustics, Ambient sounds
1 online resource (xii, 63 p.) : ill. (chiefly col.)
In passive sonar systems, knowledge of low-frequency shipping noise is an important factor for target detection performance. However, an accurate model for the shipping noise structure is difficult to obtain, due to 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 for the case of a receiver below the conjugate depth. Surface shipping noise is examined using Monte Carlo simulations using a normal mode propagation model based on random distribution of ships and realistic parameters. The depth dependence of the simulated distant 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 that conventional beamforming could detect the noisy target from both direct arrival and bottom bounce in the presence of distant shipping interferers and wind noise. However, the beamwidth of conventional beamforming is wider than that of adaptive beamforming. Once the motion effects of nearby ship interferences are considered, the adaptive beamforming using diagonal loading provides better detection performance. Preliminary adaptive beamforming results corresponding to different snapshot times show that motion effects can be minimized by using short observation times.
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Li, Zizheng, "Vertical Noise Structure and Target Detection Performance in Deep Ocean Environments" (2010). Dissertations and Theses. Paper 138.