Results 181 to 190 of about 23,037 (220)

Wideband STAP (WB-STAP) for passive sonar

Oceans 2003. Celebrating the Past ... Teaming Toward the Future (IEEE Cat. No.03CH37492), 2003
This paper addresses an innovative method for passive sonar signal processing where it is required to suppress a field of moving acoustic interferes while simultaneously enhancing the signal from a weak moving source. Motivated by the Space-Time Adaptive Processing (STAP) technology for similar radar applications, we propose a solution to the passive ...
S.U. Pillai, J.R. Guerci, S.R. Pillai
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Reverse-Time Tracking to Enhance Passive Sonar

2006 9th International Conference on Information Fusion, 2006
Passive sonar depends on signals of opportunity to detect, track and localize targets. These signals are typically detected and then tracked using Kalman filter-type signal followers. Target motion analysis (TMA) is then used to estimate the target's range and, from this, its position, course and speed.
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Receiver depth selection for passive sonar systems

IEEE Journal of Oceanic Engineering, 1991
Since tactical acoustic systems such as towed arrays can be deployed at various depths, the authors address the question of what depth is optimal. This question is considered principally from the point of view of optimum propagation conditions, employing two deep-water scenarios representing summer and winter conditions in the western Mediterranean ...
C. Ferla, M.B. Porter
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PASSIVE SONAR PERFORMANCE ENGINE (SPE)

VALIDATION OF SONAR PERFORMANCE ASSESSMENT TOOLS 2010, 2023
KD HEANEY, RL CAMPBELL
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Optimum Spatial Processing of Passive Sonar Signals

IEEE Transactions on Aerospace and Electronic Systems, 1978
The spatial structure of the likelihood ratio array processor for detecting a monochromatic plane wave signal in Gaussian noise is compared with a conventional beam-forming detector. Conditions are determined under which the optimum detector performs significantly better than the conventional detector.
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Machine learning approach to passive sonar localization.

The Journal of the Acoustical Society of America, 2011
A machine learning-based depth classifier for passive sonar is under development. The classifier is based on a support vector machine (SVM) paired with backward feature selection through margin-based feature elimination (MFE). The overcomplete feature space consists of features that have been shown to work in other passive sonar classifiers, features ...
Brett E. Bissinger, R. Lee Culver
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Holographic Passive Sonar

IEEE Transactions on Sonics and Ultrasonics, 1977
K. Sasaki, T. Sato, Y. Nakamura
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From acoustic observatories to robust passive sonar

The Journal of the Acoustical Society of America, 2003
The evolution of the DARPA Robust Passive Sonar (RPS) as well as the ONR Shallow Water Acoustic Testbed (SWAT) programs can be traced from concept of an acoustic observatory posed by Munk in 1980 through several assessment and feasibility studies to their current implementations. During this, the thinking on several key hypotheses matured.
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Wideband Robust Capon Beamforming for Passive Sonar

IEEE Journal of Oceanic Engineering, 2013
In passive sonar, narrowband adaptive beamforming techniques can be exploited to increase the signal-to-interference-plus-noise ratio (SINR), providing that array steering vector (ASV) errors and cross-spectral density matrix (CSDM) estimation errors can be controlled.
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A Passive Sonar for UUV Surveillance Tasks

1997
Abstract : The long-term goal is to develop a passive, autonomous, mobile system to investigate all types of noise in the ocean, both man-made and naturally occurring. The information will be used to improve the understanding of the noise field and the environmental factors which affect the propagation of underwater sound in coastal regions.
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