Browsing by Author "Martins, N."
Now showing 1 - 10 of 19
Results Per Page
Sort Options
- A time-frequency approach to blind deconvolution in multipath underwater channelsPublication . Martins, N.; Jesus, S. M.; Gervaise, C.; Quinquis, A.Blind deconvolution is presented in the underwater acoustic channel context, by time-frequency processing. The acoustic propagation environment was modelled as a multipath propagation channel. For noiseless simulated data, source signature estimation was performed by a model-based method. The channel estimate was obtained via a time-frequency formulation of the conventional matched-filter. Simulations used a ray-tracing physical model, initiated with at-sea recorded environmental data, in order to produce realistic underwater channel conditions. The quality of the estimates was 0.793 for the source signal, and close to I for the resolved amplitudes and time-delays of the impulse response. Time-frequency processing has proved to overcome the typical ill-conditioning of single sensor deterministic deconvolution techniques.
- Acoustic field calibration for noise prediction: the CALCOM'10 data setPublication . Martins, N.; Felisberto, P.; Jesus, S. M.Wave energy is one of the marine renewable energies that are becoming increasingly explored. One of the concerns about the respective ocean plants is the noise generated by the mechanical energy converters. This noise may affect the fauna surrounding the energy plant, what induces the idea of planning the location of a prospective plant, optimum in terms of noise minimization. Naturally, in such an approach, the plant noise can be predicted, using information concerning the ocean geometric, water column and bottom properties, if available. This information can be fed to an acoustic propagation code, to solve an acoustic forward problem. Inevitably, this knowledge is often incomplete, and the use of guesses or inferences from nautical charts can lead to erroneous noise predictions. This paper presents a noise prediction tool which can be divided into two steps. The first step consists of characterizing the candidate ocean area, in terms of the environmental properties relevant to acoustic propagation. In the second step, the environmental characteristics are fed to a computational acoustic propagation model, which provides estimates of the plant-noise generated in the candidate area. The first step uses at-sea measured acoustic data, during the CALCOM’10 sea trial (in Portugal), to solve an acoustic inverse problem, which gives environmental estimates. This procedure can be seen as a “field model calibration”, in that the estimated environmental properties are tailored to model the acoustic data. The second step uses the estimates in a forward modeling problem, with the same propagation code. In numerical terms, differences greater than 4.4 dB in the median of the modeled transmission loss difference have been observed, upto 1.6 km from the acoustic source. The results show that the field calibration is important to better model the data at hand, and thus act as a noise prediction tool, as compared to a procedure in which only a partial a priori knowledge of the candidate oceanic area is available. The results are promising, in terms of the application of the present method in the project of ocean power plants.
- Acoustic rapid environmental assessment: the AOB conceptPublication . Jesus, S. M.; Soares, C.; Martins, N.Rapidly assessing the environmental conditions of a given coastal area with the capability of being able to predict its evolution in the next 24 or 48 hours has been the goal of many initiatives since the end of the cold war and the shift of strategic regions to shallow areas. Most efforts were carried out by oceanographic teams feeding data of various nature (currents, SST, temperature, altimetry, wave height, etc...) into small scale circulation models (such as mini HOPS and NCOM). Testing has been going on for several years on the validation of such models in various scenarios. Among others, the goal of this testing is to decrease the error variance of various environmental parameter predictions at 1, 2 or 3 days with a minimal model initialization.
- Bayesian acoustic prediction assimilating oceanographic and acoustically inverted dataPublication . Martins, N.; Jesus, S. M.The prediction of the transmission loss evolution on a day to week frame, in a given oceanic area, is an important issue in modeling the sonar performance. It relies primarily on acoustic propagation models, which convert water column and geometric/ geoacoustic parameters to ‘instantaneous’ acoustic field estimates. In practice, to model the acoustic field, even the most accurate acoustic models have to be fed with simplified environmental descriptions, due to computational issues and to a limited knowledge of the environment. This is a limitation, for example, in acoustic inversion methods, in which, by maximizing the proximity between measured and modeled acoustic signals, the estimated environmental parameters are deviated from reality, forming what is normally called an ‘acoustically equivalent environment’. This problem arises also in standard acoustic prediction, in which, the oceanographic forecasts and bottom data (typically from archives) are fed directly to an acoustic model. The claim in the present work is that, by converting the oceanographic prediction and the bottom properties to ‘acoustically equivalent’ counterparts, the acoustic prediction can be obtained in an optimal way, adapted to the environmental model at hand. Here, acoustic prediction is formulated as a Bayesian estimation problem, in which, the observables are oceanographic forecasts, a set of known bottom parameters, a set of acoustic data, and a set of water column data. The predictive posterior PDF of the future acoustic signal is written as a function of elementary PDF functions relating these observables and ‘acoustically equivalent’ environmental parameters. The latter are obtained by inversion of acoustic data. The concept is tested on simulated data based on water column measurements and forecasts for the MREA’03 sea trial.
- Blind channel estimation with data from the INTIMATE'96 sea trialPublication . Martins, N.; Jesus, S. M.Blind multipath channel estimation is studied by time-frequency (TF) analysis. For a linear frequency modulated source, the technique is based on its instantaneous frequency estimation, followed by an approximate formulation of matched- ltering. Tests concern at-sea recorded data during the INTIMATE '96 experiment.
- Blind estimation of the ocean acoustic channel by time-frequency processingPublication . Martins, N.; Jesus, S. M.A blind estimator of the ocean acoustic channel impulse response envelope is presented. The signal model is characterized by a deterministic multipath channel excited by a highly nonstationary deterministic source signal. The time–frequency (TF) representation of the received signal allows for the separation between the channel and the source signal. The proposed estimator proceeds in two steps: First, the unstable initial arrivals allow for the estimation of the source signal instantaneous frequency (IF) by maximization of the radially Gaussian kernel distribution; then, the Wigner–Ville distribution (WV) is sequentially windowed and integrated, where the window is defined by the previously estimated IF. The integral gives the channel impulse response envelope, which turns to be an approximation to the blind conventional matched filter (MF). The blind channel estimator (CE) is applicable upon the following conditions: that the multipath channel contains at least one dominant arrival well separated from the others, and that the IF of the source signal is a one-to-one function. Results obtained on real data from the INternal TIde Measurements with Acoustic Tomography Experiments (INTIMATE’ 96), where the acoustic channel was driven by an linear frequency modulation signal, show that the channel’s envelope detailed structure could be accurately and consistently recovered, with the correlation of the estimates ranging from 0.796 to 0.973, as compared to the MF result.
- Classification of three-dimensional ocean features using three-dimensional empirical orthogonal functionsPublication . Martins, N.; Calado, L.; Paula, A. C. de; Jesus, S. M.Acoustic tomography is now a well known method for remote estimation of water column properties. The problem is ill-conditioned and computationally intensive, if each spatial point varies freely in the inversion. Empirical orhogonal functions (EOFs) efficiently regularize the inversion, leading to a few (2, 3) coefficients to be estimated, giving a coherent estimate of the field. At small scales, EOFs are typically depth-dependent basis functions. The extension of the concept to larger-scale anisotropic fields requires horizontal discretization into cells, with corresponding coefficients. This becomes unstable and computationally intensive, having been overcome by two-dimensional depth-range EOFs, in the past. The present work extends the empirical orthogonal function concept to three dimensions, assessing the performance of the inversion for an instantaneous sound speed field constructed from dynamical predictions for Cabo Frio, Brazil. The results show that the large-scale features of the field are correctly estimated, though with strong ambiguity, using an acoustic source tens of km from an acoustic hydrophone array. Work is under progress, to remove the ambiguity and estimate finer details of the three-dimensional field, via the addition of multiple acoustic arrays.
- Environmental and acoustic assessment: The AOB conceptPublication . Martins, N.; Soares, C.; Jesus, S. M.The requirement for rapid environmental assessment has motivated the development of prediction tools, which allow the observation and prediction in very short notice, of the ocean evolution in an interval up to 3-4 weeks, in given littoral areas. Complex systems exist nowadays, where multidimensional quantities like the oceanographic-biogeochemical-optical-acoustic fields, are tracked in time, melding measures and models of some or all the involved quantities. At some point in the prediction system, the acoustic forecast is computed by acoustic propagation models taking as input the environmental forecast. Inevitably, the error of the acoustic forecast as given by the model output, originates from at least two error sources. The first is the environmental forecast error. The second is due to the model inaccuracies, and to the dependence of propagation on parameters not dealt with by the prediction system, like geometric or geo-acoustic properties. The acoustic community has developed a large number of acoustic inversion systems - based on e.g. matched-field processors or travel-time tomography - from which one can learn that an accurate acoustic simulation requires feeding the acoustic model with an environment which differs from the actual environment by a certain gap. This requires that the environmental forecast as given by ocean prediction systems be gap-compensated, prior to its inclusion in the acoustic environmental input. This paper puts the environmental gap in evidence, considering environmental forecasts, and historical and inverted data, to define heterogeneous environmental inputs to the propagation model. The corresponding acoustic outputs are compared to actual data from the MREA '03 sea trial. It is observed that acoustic inversion can play a significant role in converting the environmental forecast into the acoustic forecast. (c) 2007 Elsevier B.V. All rights reserved.
- Estimation of anisotropic temperature perturbation statistics of MREA'03 data'', Acoustic - Oceanographic Buoy - AOBPublication . Martins, N.In order to oceanographically map a given area, deterministic models of oceanographic processes have been coupled with statistical interpolation tools, to overcome the sparsity of oceanographic measurements. These tools assume some prescribed model for the inter-correlation between physical quantities. One characteristic model –a modified Gaussin with space-time dependence–, is here fitted to temperature data correlations from the MREA ’03 sea trial. The model is parameterized by four correlation lengths and a scaling factor. The model was fitted to two differently originated data correlations: one, from data measured by a spatially fixed single instrument or by CTD casts in the area; the other, from stacked data measured by all temperature monitoring instruments. The results show that the actual temperature perturbation field is not homogeneous, nor stationary, what was expected. The determination of the horizontal correlation lags was possible only via the combination of multiple-instrument data.
- Field calibration a tool for acoustic noise prediction. The CALCOM 10 data setPublication . Felisberto, P.; Jesus, S. M.; Martins, N.It is widely recognized that anthropogenic noise affects the marine fauna, thus it becomes a major concern in ocean management policies. In the other hand there is an increasing demand for wave energy installations that, presumably, are an important source of noise. A noise prediction tool is of crucial importance to assess the impact of a perspective installation. Contribute for the development of such a tool is one of the objectives of the WEAM project. In this context, the CALCOM’10 sea trial took place off the south coast of Portugal, from 22 to 24 June, 2010 with the purpose of field calibration. Field calibration is a concept used to tune the parameters of an acoustic propagation model for a region of interest. The basic idea is that one can significantly reduce the uncertainty of the predictions of acoustic propagation in a region, even with scarce environmental data (bathymetric, geoacoustic), given that relevant acoustic parameters obtained by acoustic inference (i.e. acoustic inversion) are integrated in the prediction scheme. For example, this concept can be applied to the classical problem of transmission loss predictions or, as in our case, the problem of predicting the distribution of acoustic noise due to a wave energy power plant. In such applications the accuracy of bathymetric and geoacoustic parameters estimated by acoustic means is not a concern, but only the uncertainty of the predicted acoustic field. The objective of this approach is to reduce the need for extensive hydrologic and geoacoustic surveys, and reduce the influence of modelling errors, for example due to the bathymetric discretization used. Next, it is presented the experimental setup and data acquired during the sea trial as well as preliminary results of channel characterization and acoustic forward modelling.