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Preston J.R.,Pennsylvania State University | Abraham D.A.,CausaSci LLC
IEEE Journal of Oceanic Engineering | Year: 2015

False alarms arising from sonar clutter are one of the primary limitations to the use of active sonar in shallow-water environments. A statistical analysis of experimental data obtained for one type of clutter - echoes from a shipwreck - is presented in this paper. In the experiment, multistatic sonar measurements of a shipwreck were taken at three different ranges, over a wide variety of aspect angles and bistatic angles. The echo envelope statistics were characterized in terms of the K -distribution shape parameter (α) with an average value of approximately 2 measured for the closest range. While smaller values of α were observed at beam aspects, variations with range and bistatic angle were predominantly explained by related variations in signal-to-noise ratio (SNR). Additionally, estimates of α from each range were seen to be log-normally distributed, including the variation with aspect and SNR. © 1976-2012 IEEE. Source


Lyons A.P.,Pennsylvania State University | Abraham D.A.,CausaSci LLC | Johnson S.F.,Johns Hopkins University
IEEE Journal of Oceanic Engineering | Year: 2010

The characterization and modeling of synthetic aperture sonar (SAS) image statistics is of importance for developing target-on-background detection and classification algorithms and for developing specialized filters for speckle noise reduction. In this paper, we present a model to predict the impact of amplitude scaling caused by seafloor ripples on SAS image speckle statistics. The continuous variation in scattering strength produced by ripples (i.e., ripple-induced changes in seafloor slope) is treated as deterministic amplitude scaling on image speckle produced by the SAS imaging process. Changes in image statistics caused by ripples are quantified in terms of an effective K-distribution shape parameter. Agreement between shape parameter estimated from the scaling model and from SAS data collected in experiments off Panama City, FL and off the Ligurian coast near La Spezia, Italy illustrate the efficacy of the model. © 2010 IEEE. Source


Abraham D.A.,CausaSci LLC | Lyons A.P.,Pennsylvania State University
IEEE Journal of Oceanic Engineering | Year: 2010

Parameter estimation for the K -distribution is an essential part of the statistical analysis of non-Rayleigh sonar reverberation or clutter for performance prediction, estimation of scattering properties, and for use in signal and information processing algorithms. Computational issues associated with maximum-likelihood (ML) estimation techniques for K -distribution parameters often force the use of the method of moments (MoM). However, as often as half the time, MoM techniques will fail owing to a noninvertible equation relating the shape parameter α to a particular moment ratio, which is equivalent to the detection index D of the matched-filter envelope. In this paper, a Bayesian approach is taken in developing a MoM-based estimator for D, and therefore α, that reliably provides a solution and is less computationally demanding than the ML techniques. Analytical-approximation (AA) and bootstrap-based (BB) approaches are considered for approximating the likelihood function of D; and forming a posterior mean estimator, which is compared with the standard MoM and ML techniques. Computational complexity (in the form of execution time) for the BayesMoMAA estimator is on the order of the standard MoM estimator while the BayesMoMBB estimator can be 12 orders of magnitude greater, although still less than ML techniques. Performance is seen to be better than the standard MoM approach and the ML techniques, except for very small α(<3) where the ML techniques remain superior. Advantages of the Bayesian approach are illustrated through the use of alternative priors, the formation of Bayesian confidence intervals, and a technique for combining estimates from multiple experiments. © 2010 IEEE. Source


Abraham D.A.,CausaSci LLC
IEEE Journal of Oceanic Engineering | Year: 2010

The detection-threshold (DT) term in the sonar equation describes the signal-to-noise ratio (SNR) required to achieve a specified probability of detection Pd for a given probability of false alarm Pfa. Direct evaluation of DT requires obtaining the fadetector threshold h as a function of Pfa and then using h while inverting the often complicated relationship between SNR and Pd. However, easily evaluated approximations to DT exist when the background additive noise or reverberation is Gaussian (i.e., has a Rayleigh-distributed envelope). While these approximations are extremely accurate for Gaussian backgrounds, they are erroneously low when the background has a heavy-tailed probability density function. In this paper, it is shown that by obtaining h appropriately from the non-Gaussian background while approximating P d for a target in the non-Gaussian background by that for a Gaussian background, the easily evaluated approximations to DT extend to non-Gaussian backgrounds with minimal loss in accuracy. Both fluctuating targets (FTs) and nonfluctuating targets (NFTs) are considered in Weibull- and K-distributed backgrounds. While the pd approximation for FTs is very accurate, it is coarser for NFTs, necessitating a correction factor to the DT approximations. © 2010 IEEE. Source


Abraham D.A.,CausaSci LLC | Lyons A.P.,Pennsylvania State University
IEEE Journal of Oceanic Engineering | Year: 2010

The special of IEEE Journal of Oceanic Engineering has published a number of papers that focus on non-Rayleigh reverberation and clutter. It is found that 11 of the 18 papers analyze or present real data: five in low- or mid-frequency systems in relation to real data analysis, while five deal with high-frequency systems and one with sea-surface radar data. The pdf models encountered in this special issue include, Rayleigh, , Weibull, Rayleigh mixture, log-normal, extreme-value, generalized Pareto, gamma, exponential, and Poisson Rayleigh. A team of researchers presents a statistical analysis of backscatter derived from data collected with a multibeam sonar system from sand and rhodolith-covered seabeds. The backscatter envelope distribution has been seen to be essentially Rayleigh for the sandy bed at all incidence-angle groups, while the rhodolith-covered bed presents non-Rayleigh pdfs only at the higher incidence angles. Source

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