Particle filtering for passive fathometer tracking
نویسندگان
چکیده
منابع مشابه
Particle filtering for passive fathometer tracking.
Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model partic...
متن کاملPassive fathometer processing.
Ocean acoustic noise can be processed efficiently to extract Green's function information between two receivers. By using noise array-processing techniques, it has been demonstrated that a passive array can be used as a fathometer [Siderius, et al., J. Acoust. Soc. Am. 120, 1315-1323 (2006)]. Here, this approach is derived in both frequency and time domains and the output corresponds to the ref...
متن کاملAdaptive passive fathometer processing.
Recently, a technique has been developed to image seabed layers using the ocean ambient noise field as the sound source. This so called passive fathometer technique exploits the naturally occurring acoustic sounds generated on the sea-surface, primarily from breaking waves. The method is based on the cross-correlation of noise from the ocean surface with its echo from the seabed, which recovers...
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Particle filtering is a sequential Monte Carlo technique that recursively computes the posterior probability density function using the concept of “Importance Sampling”. This paper considers the application of particle filtering technique to a target tracking application, in which a radar sends a signal towards a target and estimates the state (position and velocity) of the target using the obs...
متن کاملMultiple Model Particle Filtering for Multitarget Tracking
This paper addresses the problem of tracking multiple moving targets by recursively estimating the joint multitarget probability density (JMPD). Estimation of the JMPD is done in a Bayesian framework, providing a method of tracking multiple targets which allows nonlinear target motion, nonlinear measurement to state coupling, and non-Gaussian target state densities. We utilize a particle filter...
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ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 2012
ISSN: 0001-4966
DOI: 10.1121/1.3670004