Performance analysis of subspace based method for source localization in shallow water

The present paper aims at studying the performance characteristics of a subspace based algorithm for source localization in shallow water such as coastal water. Specifically, we study the performance of Multi Image Subspace Algorithm (MISA). Through first-order perturbation analysis and computer simulation it is shown that MISA is unbiased and statistically efficient. Further, we bring out the role of multipaths (or images) in reducing the error in the localization. It is shown that the presence of multipaths is found to improve the range and depth estimates. This may be attributed to the increased curvature of the wavefront caused by interference from many coherent multipaths.

Source localization in a partially known shallow?water channel

The source localization in shallow water is beset with problems arising from the presence of a large number of correlated multipaths. Nevertheless, given a complete knowledge of the water channel it is definitely possible to localize a source. A complete knowledge of the channel, however, is rarely available under most practical conditions. A new approach is proposed wherein the bottom reflection coefficients are not required; hence the bottom conditions need not be known. Further, because of the use of signal subspace for localization, the proposed approach is robust against the background noise (-20 dB) and channel depth uncertainty (10 lambda). All these nice features of the proposed approach are possible only when the array size is large (>40 sensors). (C) 1995 Acoustical Society of America.

Localization induced base isolation in fractionally damped non linear system

In the present article we take up the study of nonlinear localization induced base isolation of a 3 degree of freedom system having cubic nonlinearities under sinusoidal base excitation. The damping forces in the system are described by functions of fractional derivative of the instantaneous displacements, typically linear and quadratic damping are considered here separately. Under the assumption of smallness of certain system parameters and nonlinear terms an approximate estimate of the response at each degree of freedom of the system is obtained by the Method of Multiple Scales approach. We then consider a similar system where the nonlinear terms and certain other parameters are no longer small. Direct numerical simulation is made use of to obtain the amplitude plot in the frequency domain for this case, which helps us to establish the efficacy of this method of base isolation for a broad class of systems. Base isolation obtained this way has no counterpart in the linear theory.

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.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Multiple transmitter localization and communication footprint identification using sparse reconstruction techniques

This paper considers the problem of identifying the footprints of communication of multiple transmitters in a given geographical area. To do this, a number of sensors are deployed at arbitrary but known locations in the area, and their individual decisions regarding the presence or absence of the transmitters' signal are combined at a fusion center to reconstruct the spatial spectral usage map. One straightforward scheme to construct this map is to query each of the sensors and cluster the sensors that detect the primary's signal. However, using the fact that a typical transmitter footprint map is a sparse image, two novel compressive sensing based schemes are proposed, which require significantly fewer number of transmissions compared to the querying scheme. A key feature of the proposed schemes is that the measurement matrix is constructed from a pseudo-random binary phase shift applied to the decision of each sensor prior to transmission. The measurement matrix is thus a binary ensemble which satisfies the restricted isometry property. The number of measurements needed for accurate footprint reconstruction is determined using compressive sampling theory. The three schemes are compared through simulations in terms of a performance measure that quantifies the accuracy of the reconstructed spatial spectral usage map. It is found that the proposed sparse reconstruction technique-based schemes significantly outperform the round-robin scheme.

Multi-script and multi-oriented text localization from scene images

This paper describes a new method of color text localization from generic scene images containing text of different scripts and with arbitrary orientations. A representative set of colors is first identified using the edge information to initiate an unsupervised clustering algorithm. Text components are identified from each color layer using a combination of a support vector machine and a neural network classifier trained on a set of low-level features derived from the geometric, boundary, stroke and gradient information. Experiments on camera-captured images that contain variable fonts, size, color, irregular layout, non-uniform illumination and multiple scripts illustrate the robustness of the method. The proposed method yields precision and recall of 0.8 and 0.86 respectively on a database of 100 images. The method is also compared with others in the literature using the ICDAR 2003 robust reading competition dataset.

Strain localization effect on system reliability based design of bridge abutments under earthquake loading

The component and system reliability based design of bridge abutments under earthquake loading is presented in the paper. Planar failure surface has been used in conjunction with pseudo-dynamic approach to compute seismic active earth pressures on an abutment. The pseudo-dynamic method, considers the effect of phase difference in shear waves, soil amplification along with the horizontal seismic accelerations, strain localization in backfill soil and associated post-peak reduction in the shear resistance from peak to residual values along a previously formed failure plane. Four modes of stability viz. sliding, overturning, eccentricity and bearing capacity of the foundation soil are considered in the analysis. The series system reliability is computed with an assumption of independent failure modes. The lower and upper bounds of system reliability are also computed by taking into account the correlations between four failure modes, which is evaluated using the direction cosines of the tangent planes at the most probable points of failure.

Influence of strain localization on reliability based design of bridge abutments using pseudo-dynamic method

The paper focuses on reliability based design of bridge abutments when subjected to earthquake loading. Planar failure surface has been used in conjunction with pseudo-dynamic approach to compute the seismic active earth pressures on the bridge abutment. The proposed pseudo dynamic method, considers the effects of strain localization in the backfill soil and associated post-peak reduction in the shear resistance from peak to residual values along a previously formed failure plane, phase difference in shear waves and soil amplification along with the horizontal seismic accelerations. Four modes of stability viz. sliding, overturning, eccentricity and bearing capacity of the foundation soil are considered for the reliability analysis. The influence of various design parameters on the seismic reliability indices against four modes of failure is presented, following the suggestions of Japan Road Association, Caltrans Bridge Design Specifications and U.S Department of the Army.

Longitudinal localization of tropical intraseasonal variability

Intraseasonal time-scales play an important role in tropical variability. Two modes that contribute significantly to tropical intraseasonal variability (ISV) are the eastward-propagating MaddenJulian Oscillation (MJO), and westward-moving moist equatorial Rossby waves. This note reports on a correspondence between the longitudinal gradient of mean tropical precipitable water (PW), and the geographical regions of genesis, and convective activity, of both these large-scale tropical systems. Our finding is based on an analysis of PW from the MERRA reanalysis product. The data indicate that the mean tropical PW has a dominant wavenumber two (three) structure in longitude in the Northern (Southern) Hemisphere. Departures from a longitudinally homogeneous state are attributed to the influence of subtropical anticyclones, and are accentuated by monsoonal regions of both hemispheres. This mean structure results in a sharply localized longitudinal gradient of PW. Remarkably, regions with positive gradients (such as the Northern and Southern Hemisphere western Indian Ocean), i.e. they have larger PW to the east, are the very zones that are implicated in the formation, and show high levels of convective activity, of the eastward-moving MJO. On the other hand, regions with negative gradients (such as the Southern Hemisphere central Pacific) are the very regions where genesis, and maxima in variance, of westward-moving moist equatorial Rossby waves are known to occur. Apart from providing a first-order longitudinal footprint of the convective phase of these systems, this correspondence reinforces the role of the mean climatic state in tropical ISV. Copyright (c) 2012 Royal Meteorological Society

Spectral zero-crossings: localization properties and application to epoch extraction in speech signals

We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.