Using ocean ambient noise for array self-localization and self-synchronization

Estimates of the travel times between the elements of a bottom hydrophone array can be extracted from the time-averaged ambient noise cross-correlation function (NCF). This is confirmed using 11-min-long data blocks of ambient noise recordings that were collected in May 1995 near the southern California coast at an average depth of 21 m in the 150-700 Hz frequency range. Coherent horizontal wavefronts emerging from the time derivative of the NCF are obtained across the array's aperture and are related to the direct arrival time of the time-domain Green's function (TDGF). These coherent wavefronts are used for array element self-localization (AESL) and array element self-synchronization (AESS). The estimated array element locations are used to beamform on a towed source.     

Null broadening with snapshot-deficient covariance matrices in passive sonar

Adaptive-array beamforming achieves high resolution and sidelobe suppression by producing sharp s in the adaptive beampattern. Large-aperture sonar arrays with many elements have small resolution cells; interferers may move through many resolution cells in the time required for accumulating a full-rank sample covariance matrix. This leads to "snapshot-deficient" processing. In this paper, the -broadening technique originally developed for an ideal stationary problem is extended to the snapshot-deficient problem combined with white-noise constraint (WNC) adaptive processing. Null broadening allows the strong interferers to move through resolution cells and increases the number of degrees of freedom, thereby improving the detection of weak stationary signals.     

An initial demonstration of underwater acoustic communication using time reversal

In July 1999, an at-sea experiment to measure the focus of a 3.5-kHz centered time-reversal mirror (TRM) was conducted in three different environments: an absorptive bottom, a reflective bottom, and a sloping bottom. The experiment included a preliminary exploration of using a TRM to generate binary-phase shift keying communication sequences in each of these environments. Broadside communication transmissions were also made, and single-source communications were simulated using the measured-channel response. A comparison of the results is made and time reversal is shown to be an effective approach for mitigating inter-symbol interference caused by channel multipath.     

Geochemical characteristics of mineral air particles emitted inside a clay atomisation plant which introduces waste recycling processes

The objective of this work is to assess the concentrations of three factions of air particles (settable particles, TSP and PM10) and the levels of several toxic elements in a clay atomisation industry through aerosol sampling at several points inside an industrial plant. Mechanical activities, which produce diffuse emissions, are the main process of discharge of particles in both indoor and outdoor workplace environments in the atomisation plant. The levels of As, Cd, Pb, Zn, Ba and Ni increase in the zones with higher concentrations of particles and lower ventilation. The concentrations of As and F are not influenced by the recycling processes. The levels of Cd and Pb do not show great enrichment in air particles collected inside the atomisation plant although the content of both elements is associated with ceramic muck recycling. Finally, the content of B in waste water is mainly transferred in gaseous phase to the atmosphere during the process of drying by atomisation.     

COMPARISON OF MEASUREMENT METHODS BASED ON A MODEL FOR THE ERROR STRUCTURE

Comparison of methods is a technique often used for investigation of systematic errors of measurementmethods.As concerns the design and analysis of such comparisons,much variety of opinion and practiceexists.In one approach a few specimens are measured several times by different operators in differentlaboratories(reproducibility conditions)and in another approach several specimens are measured on oneor a few occasions by one operator in the same laboratory(repeatability conditions).In this paper amodel for the error structure of measurements is formulated and it is emphasized that one has todistinguish between two types of systematic errors:the first type depends only on the level of themeasured quantity and the second type is specific for the separate specimens.On the basis of this modelthe information which can be obtained from the different designs of method comparisons is discussed.A new approach for the analysis of method comparisons with many specimens is also proposed.     

Appraisal of soft computing techniques in prediction of total bed material load in tropical rivers

This paper evaluates the performance of three soft computing techniques, namely Gene-Expression Programming (GEP) (Zakaria et al 2010), Feed Forward Neural Networks (FFNN) (Ab Ghani et al 2011), and Adaptive Neuro-Fuzzy Inference System (ANFIS) in the prediction of total bed material load for three Malaysian rivers namely Kurau, Langat and Muda. The results of present study are very promising: FFNN (R ² = 0.958, RMSE = 0.0698), ANFIS (R ² = 0.648, RMSE = 6.654), and GEP (R ² = 0.97, RMSE = 0.057), which support the use of these intelligent techniques in the prediction of sediment loads in tropical rivers.     

An overview of matched field methods in ocean acoustics

A short historical overview of matched-field processing (MFP) is followed by background material in both ocean acoustics and array processing needed for MFP. Specific algorithms involving both quadratic and adaptive methods are then introduced. The results of mismatch studies and several algorithms designed to be relatively robust against mismatch are discussed. The use of simulated MFP for range, depth and bearing location is examined, using data from a towed array that has been tilted to produce an effective vertical aperture. Several experiments using MFP are reviewed. One successfully demonstrated MFP at megameter ranges; this has important consequences for experiments in global tomography. Some unique applications of MFP, including how it can exploit ocean inhomogeneities and make tomographic measurements of environmental parameters, are considered     

Beam forming on bottom-interacting tow-ship noise

Ship noise received on a horizontal array towed behind the ship is shown to be useful as a potentially diagnostic tool for estimating local acoustic bottom properties. In numerical simulations, tow-ship noise which bounces off the bottom is processed on a beamformer that shows the arrival angles; the beamformer output is readily interpreted by relating it to the Green's function of the acoustic wave equation. Simple signal processing is shown to be sufficient to extract the propagation angles of the "trapped" (i.e., propagating) modes of the acoustic waveguide. By relating the trapped modes to a basic geophysical model of the bottom, one can predict acoustic-propagation conditions for a particular bottom-interacting ocean acoustic environment.     

Improvement of Time-Reversal Communications Using Adaptive Channel Equalizers

The spatial and temporal focusing properties of time-reversal methods can be exploited for undersea acoustic communications. Spatial focusing mitigates channel fading and produces a high signal-to-noise ratio (SNR) at the intended receivers along with a low probability of interception elsewhere. While temporal focusing (compression) reduces significantly intersymbol interference (ISI), there always is some residual ISI depending upon the number of transmitters, their spatial distribution (spatial diversity), and the complexity of the channel. Moreover, a slight change in the environment over the two-way propagation interval introduces additional ISI. Using multilevel quadrature amplitude modulation (M-QAM) in shallow water, we demonstrate that the performance of time-reversal communications can be improved significantly by cascading the received time series with an adaptive channel equalizer to remove the residual ISI     

Bedload transport of small rivers in Malaysia

Numerous time-consuming equations, based on the relationship between the reliability and representativeness of the data utilized in defining variables and constants, require complex parameters to estimate bedload transport. In this study the easily accessible data including flow discharge, water depth, water surface slope, and surface grain diameter （ds0） from small rivers in Malaysia were used to estimate bedload transport. Genetic programming （GP） and artificial neural network （ANN） models are applied as complementary tools to estimate bed load transport based on a balance between simplicity and accuracy in small rivers. The developed models demonstrate higher performance with an overall accuracy of 97% and 93% for ANN and GP, respectively compared with other traditional methods and empirical equations.