974 resultados para Radar - Detecção automatica


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Ballast fouling is created by the breakdown of aggregates or outside contamination by coal dust from coal trains, or from soil intrusion beneath rail track. Due to ballast fouling, the conditions of rail track can be deteriorated considerably depending on the type of fouling material and the degree of fouling. So far there is no comprehensive guideline available to identify the critical degree of fouling for different types of fouling materials. This paper presents the identification of degree of fouling and types of fouling using non-destructive testing, namely seismic surface-wave and ground penetrating radar (GPR) survey. To understand this, a model rail track with different degree of fouling has been constructed in Civil engineering laboratory, University of Wollongong, Australia. Shear wave velocity obtained from seismic survey has been employed to identify the degree of fouling and types of fouling material. It is found that shear wave velocity of fouled ballast increases initially, reaches optimum fouling point (OFP), and decreases when the fouling increases. The degree of fouling corresponding after which the shear wave velocity of fouled ballast will be smaller than that of clean ballast is called the critical fouling point (CFP). Ground penetrating radar with four different ground coupled antennas (500 MHz, 800 MHz, 1.6 GHz and 2.3 GHz) was also used to identify the ballast fouling condition. It is found that the 800 MHz ground coupled antenna gives a better signal in assessing the ballast fouling condition. Seismic survey is relatively slow when compared to GPR survey however it gives quantifiable results. In contrast, GPR survey is faster and better in estimating the depth of fouling. (C) 2011 Elsevier B.V. All rights reserved.

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This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

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This paper discusses the use of Jason-2 radar altimeter measurements to estimate the Ganga-Brahmaputra surface freshwater flux into the Bay of Bengal for the period mid-2008 to December 2011. A previous estimate was generated for 1993-2008 using TOPEX-Poseidon, ERS-2 and ENVISAT, and is now extended using Jason-2. To take full advantages of the new availability of in situ rating curves, the processing scheme is adapted and the adjustments of the methodology are discussed here. First, using a large sample of in situ river height measurements, we estimate the standard error of Jason-2-derived water levels over the Ganga and the Brahmaputra to be respectively of 0.28 m and 0.19 m, or less than similar to 4% of the annual peak-to-peak variations of these two rivers. Using the in situ rating curves between water levels and river discharges, we show that Jason-2 accurately infers Ganga and Brahmaputra instantaneous discharges for 2008-2011 with mean errors ranging from similar to 2180 m(3)/s (6.5%) over the Brahmaputra to similar to 1458 m(3)/s (13%) over the Ganga. The combined Ganga-Brahmaputra monthly discharges meet the requirements of acceptable accuracy (15-20%) with a mean error of similar to 16% for 2009-2011 and similar to 17% for 1993-2011. The Ganga-Brahmaputra monthly discharge at the river mouths is then presented, showing a marked interannual variability with a standard deviation of similar to 12500 m(3)/s, much larger than the data set uncertainty. Finally, using in situ sea surface salinity observations, we illustrate the possible impact of extreme continental freshwater discharge event on the northern Bay of Bengal as observed in 2008.

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We report novel resistor grid network based space cloth for application in single and multi layer radar absorbers. The space cloth is analyzed and relations are derived for the sheet resistance in terms of the resistor in the grid network. Design curves are drawn using MATLAB and the space cloth is analyzed using HFSS™ software in a Salisbury screen for S, C and X bands. Next, prediction and simulation results for a three layer Jaumann absorber using square grid resistor network with a Radar Cross Section Reduction (RCSR) of -15 dB over C, X and Ku bands is reported. The simulation results are encouraging and have led to the fabrication of prototype broadband radar absorber and experimental work is under progress.

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Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

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Comparison of reflectivity data of radars onboard CloudSat and TRMM is performed using coincident overpasses. The contoured frequency by altitude diagrams (CFADs) are constructed for two cases: (a) only include collocated vertical profiles that are most likely to be raining and (b) include all collocated profiles along with cloudy pixels falling within a distance of about 50 km from the centre point of coincidence. Our analysis shows that for both cases, CloudSat underestimates the radar reflectivity by about 10 dBZ compared to that of TRMM radar below 15 km altitude. The difference is well outside the uncertainty value of similar to 2 dBZ of each radar. Further, CloudSat reflectivity shows a decreasing trend while that of TRMM radar an increasing trend below 4 km height. Basically W-band radar that CloudSat flies suffers strong attenuation in precipitating clouds and its reflectivity value rarely exceeds 20 dBZ though its technical specification indicates the upper measurement limit to be 40 dBZ. TRMM radar, on the other hand, cannot measure values below 17 dBZ. In fact combining data from these two radars seems to give a better overall spatial structure of convective clouds.

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Identification and mapping of crevasses in glaciated regions is important for safe movement. However, the remote and rugged glacial terrain in the Himalaya poses greater challenges for field data collection. In the present study crevasse signatures were collected from Siachen and Samudra Tapu glaciers in the Indian Himalaya using ground-penetrating radar (GPR). The surveys were conducted using the antennas of 250 MHz frequency in ground mode and 350 MHz in airborne mode. The identified signatures of open and hidden crevasses in GPR profiles collected in ground mode were validated by ground truthing. The crevasse zones and buried boulder areas in a glacier were identified using a combination of airborne GPR profiles and SAR data, and the same have been validated with the high-resolution optical satellite imagery (Cartosat-1) and Survey of India mapsheet. Using multi-sensor data, a crevasse map for Samudra Tapu glacier was prepared. The present methodology can also be used for mapping the crevasse zones in other glaciers in the Himalaya.

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Radar services are occasionally affected by wind farms. This paper presents a comprehensive description of the effects that a wind farm may cause on the different radar services, and it compiles a review of the recent research results regarding the mitigation techniques to minimize this impact. Mitigation techniques to be applied at the wind farm and on the radar systems are described. The development of thorough impact studies before the wind farm is installed is presented as the best way to analyze in advance the potential for interference, and subsequently identify the possible solutions to allow the coexistence of wind farms and radar services.

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Two high-frequency (HF) radar stations were installed on the coast of the south-eastern Bay of Biscay in 2009, providing high spatial and temporal resolution and large spatial coverage of currents in the area for the first time. This has made it possible to quantitatively assess the air-sea interaction patterns and timescales for the period 2009-2010. The analysis was conducted using the Barnett-Preisendorfer approach to canonical correlation analysis (CCA) of reanalysis surface winds and HF radar-derived surface currents. The CCA yields two canonical patterns: the first wind-current interaction pattern corresponds to the classical Ekman drift at the sea surface, whilst the second describes an anticyclonic/cyclonic surface circulation. The results obtained demonstrate that local winds play an important role in driving the upper water circulation. The wind-current interaction timescales are mainly related to diurnal breezes and synoptic variability. In particular, the breezes force diurnal currents in waters of the continental shelf and slope of the south-eastern Bay. It is concluded that the breezes may force diurnal currents over considerably wider areas than that covered by the HF radar, considering that the northern and southern continental shelves of the Bay exhibit stronger diurnal than annual wind amplitudes.

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The problem of finding the depths of glaciers and the current methods are discussed briefly. Radar methods are suggested as a possible improvement for, or adjunct to, seismic and gravity survey methods. The feasibility of propagating electromagnetic waves in ice and the maximum range to be expected are then investigated theoretically with the aid of experimental data on the dielectric properties of ice. It is found that the maximum expected range is great enough to measure the depth of many glaciers at the lower radar frequencies if there is not too much liquid water present. Greater ranges can be attained by going to lower frequencies.

The results are given of two expeditions in two different years to the Seward Glacier in the Yukon Territory. Experiments were conducted on a small valley glacier whose depth was determined by seismic sounding. Many echoes were received but their identification was uncertain. Using the best echoes, a profile was obtained each year, but they were not in exact agreement with each other. It could not be definitely established that echoes had been received from bedrock. Agreement with seismic methods for a considerable number of glaciers would have to be obtained before radar methods could be relied upon. The presence of liquid water in the ice is believed to be one of the greatest obstacles. Besides increasing the attenuation and possibly reflecting energy, it makes it impossible to predict the velocity of propagation. The equipment used was far from adequate for such purposes, so many of the difficulties could be attributed to this. Partly because of this, and the fact that there are glaciers with very little liquid water present, radar methods are believed to be worthy of further research for the exploration of glaciers.