Source localization in shallow ocean using a vertical array of acoustic vector sensors

This paper introduces a new approach to 3D localisation of a narrowband acoustic source in a shallow ocean using acoustic vector sensors (AVS). Assuming a horizontally stratified and range-independent model of the ocean, it is shown that the azimuth of the source can be determined from the estimates of the horizontal components of the acoustic intensity vector obtained from the measurements of an AVS. The range and depth of the source could then be estimated through a 2D search to match the computed complex acoustic intensity vector expressed as a function of these parameters with its estimate obtained from the AVS measurements. However the search in range is computationally intensive as the range parameter is unbounded. We propose an alternative approach employing a vertical array of AVS, based on eigen-decomposition of the spatial correlation matrix of the data vector, leading to a closed form solution for the range parameter. The source depth is then estimated through a 1D search of this bounded parameter

Improved localization of underwater acoustic sources by nonlinear wavelet denoising under non-Gaussian noise conditions

Bearing estimation of underwater acoustic sources is an important aspect of passive localization in the ocean. The performance of all bearing estimation techniques degrades under conditions of low signal-to-noise ratio (SNR) at the sensor array. The degradation may be arrested by denoising the array data before performing the task of bearing estimation. In the last few years, there has been considerable progress in the use of the wavelet transform for denoising signals. It is known that the traditionalwavelet transform, which is a linear transformation, can be used for denoising signals in Gaussian noise; but this method is not suitable if the noise is strongly non-Gaussian. Statistical measurements of ocean acoustic ambient noise data indicate that the noise may have a significantly non-Gaussian heavy-tailed distribution in some environments. In this work, we have explored the possibility of employing nonlinear wavelet denoising [1, 2], a robust technique based on median interpolation, to improve the performance of bearing estimation techniques in ocean in a strongly non-Gaussian noise environment. We propose the application of nonlinear wavelet denoising to the noisy signal at each sensor in the array to boost the SNR before performing bearing estimation by known techniques such as MUSIC and Subspace Intersection Method [3]. Simulation results are presented to show that denoising leads to a significant reduction in the mean square errors (MSE) of the estimators, and enhancement of resolution of closely spaced sources

Cramer-Rao bounds for source localization in shallow ocean with generalized Gaussian noise

Localization of underwater acoustic sources is a problem of great interest in the area of ocean acoustics. There exist several algorithms for source localization based on array signal processing.It is of interest to know the theoretical performance limits of these estimators. In this paper we develop expressions for the Cramer-Rao-Bound (CRB) on the variance of direction-of-arrival(DOA) and range-depth estimators of underwater acoustic sources in a shallow range-independent ocean for the case of generalized Gaussian noise. We then study the performance of some of the popular source localization techniques,through simulations, for DOA/range-depth estimation of underwater acoustic sources in shallow ocean by comparing the variance of the estimators with the corresponding CRBs

Improved bearing estimation in ocean by nonlinear wavelet denoising under non-Gaussian noise conditions

Bearing estimation of underwater acoustic sources is an important aspect of passive localization in the ocean. The performance of all bearing estimation techniques degrades under conditions of low signal-to-noise ratio (SNR) at the sensor array. The degradation may be arrested by denoising the array data before performing the task of bearing estimation. In the last few years, there has been considerable progress in the use of the wavelet transform for denoising signals. It is known that the traditional wavelet transform, which is a linear transformation, can be used for denoising signals in Gaussian noise; but this method is not suitable if the noise is strongly non-Gaussian. Statistical measurements of ocean acoustic ambient noise data indicate that the noise may have a significantly non-Gaussian heavy-tailed distribution in some environments. In this work, we have explored the possibility of employing nonlinear wavelet denoising [1, 2], a robust technique based on median interpolation, to improve the performance of bearing estimation techniques in ocean in a strongly non-Gaussian noise environment. We propose the application of nonlinear wavelet denoising to the noisy signal at each sensor in the array to boost the SNR before performing bearing estimation by known techniques such as MUSIC and Subspace Intersection Method [3]. Simulation results are presented to show that denoising leads to a significant reduction in the mean square errors (MSE) of the estimators, and enhancement of resolution of closely spaced sources

Effect of Muons on the Phase Transition in Magnetised Proto-Neutron Star Matter

We study the effect of inclusion of muons and the muon neutrinos on the phase transition from nuclear to quark matter in a magnetised proto-neutron star and compare our results with those obtained by us without the muons. We find that the inclusion of muons changes slightly the nuclear density at which transition occurs.However the dependence of this transition density on various chemical potentials, temperature and the magnetic field remains quantitatively the same.Comment: LaTex2e file with four postscript figure

Estimation of sediment acoustic properties from horizontal array data

Oil companies conduct geophysical survey in different parts of the world. While the analysis conducted by them is directed towards determining the presence of oil in the deeper layers of the sediment, information on the shallower sediment layers that the data contains is generally ignored. In this paper we investigate the possibility of estimating the sediment properties from such data. The inversion is performed using both linear and non-linear methods. The performances of these methods are compared based on the correlation between the fields predicted by the models and the measured field

Vikara Vighata Bhava - Concept of manifestation and non manifestation of a disease

Every individual is dissimilar while resisting a disease. Disease is an outcome of mutual association between Nidanadi Visheshas (Nidana, Dosha and Dooshyas). Presence or absence of a factor called Vikara Vighata Bhava affects greatly the mutual association of Trayonidanadi Visheshas. The outcome of reaction of Nidanadi Visheshas with Vikara Vighata Bhava and Abhava will cause vivid manifestation of pathogenesis (Sampraptis). A factor which inhibits/hinders the manifestation of a disease in an individual is known as Vikara Vighata Bhava. In the absence of Vikara Vighata Bhava manifestation of a disease is possible easily

Synthesis of SmFeAsO by an Easy and Versatile Route and its Physical Property Characterization

We report synthesis, structure, electrical transport and heat capacity of SmFeAsO. The title compound is synthesized by one-step encapsulation of stoichiometric FeAs, Sm, and Sm2O3 in an evacuated (10-5 Torr) quartz tube by prolong (72 hours) annealing at 1100oC. The as synthesized compound is crystallized in tetragonal structure with P4/nmm space group having lattice parameters a = 3.93726(33) A and c = 8.49802(07) A. The resistance (R-T) measurements on the compound exhibited ground state spin-density-wave (SDW)-like metallic steps below 140 K. Heat capacity CP(T) measurements on the title compound, showed an anomaly at around 140 K, which is reminiscent of the SDW ordering of the compound. At lower temperatures the CP(T) shows a clear peak at around 4.5 K. At lower temperature below 20 K, Cp(T) is also measured under an applied field of 7 Tesla. It is concluded that the CP(T) peak at 4.5 K is due to the anti-ferromagnetic(AFM) ordering of Sm3+ spins. These results are in confirmation with ordering of Sm in Sm2-xCexCuO4.Comment: 9 pages Text + Figs Contact Author ([email protected]

An Overview On Web Scraping Techniques And Tools

From the evolution of WWW, the scenario of internet user and data exchange is fastly changes. As common people join the internet and start to use it, lots of new techniques are promoted to boost up the network. At the same time, to enhance computers and network facility new technologies were introduces which results into automatically decreasing in cost of hardware and website�s related costs. Due to all these changes, large number of users are joined and use the internet facilities. Daily use of internet cose in to a tremendous data is available on internet. Business, academician, researchers all are share their advertisements, information on internet so that they can be connected to people fastly and easily. As a result of exchange, share and store data on internet, a new problem is arise that how to handle such data overload and how the user will get or access the best information in least efforts. To solve this issues, researcher spotout new technique called Web Scraping. Web scraping is very imperative technique which is used to generate structured data on the basis of available unstructured data on the web. Scaping generated structured data then stored in central database and analyze in spreadsheets. Traditional copy-and-paste, Text grapping and regular expression matching, HTTP programming, HTML parsing, DOM parsing, Webscraping software, Vertical aggregation platforms, Semantic annotation recognizing and Computer vision web-page analyzers are some of the common techniques used for data scraping. Previously most user uses the common copy-pest technique for gathering and analyzing data on the internet, but it is a tedious technique where lot of data copied by the user and store on computer files. As compared to this technique web scraping software is easiest scraping technique. Now a days, there are lots of software are available in the market for web scraping. Our paper is focused on the overview on the information extraction technique i.e. web scraping, different techniques of web scraping and some of the recent tools used for a web scraping