Journal articles on the topic 'Radar penetrante'
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1
Ucha, J. M., M. Botelho, G. S. Vilas Boas, L. P. Ribeiro, and P. S. Santana. "Uso do radar penetrante no solo (GPR) na investigação dos solos dos tabuleiros costeiros no litoral norte do estado da Bahia." Revista Brasileira de Ciência do Solo 26, no. 2 (June 2002): 373–80. http://dx.doi.org/10.1590/s0100-06832002000200011.
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Foram estudados nove perfis ao longo de uma toposseqüência sobre os sedimentos do Grupo Barreiras, na Fazenda Rio Negro, município de Entre Rios (BA), utilizando a prospecção eletromagnética por meio do Radar Penetrante no Solo - "Ground-penetrating radar - GPR", objetivando analisar a utilização dessa ferramenta na aquisição de informações sobre as feições que ocorrem no solo, mediante a comparação entre os radargramas obtidos e a descrição pedológica. O equipamento utilizado foi um Geophysical Survey System modelo GPR SR system-2, com antena de 80 MHz. A análise radargramétrica confirmou o aparecimento dos fragipãs e duripãs em profundidade, que ocorrem sempre acompanhados de um processo de transformação dos solos do tipo Latossolo Amarelo e Argissolo Amarelo em Espodossolo. Os padrões de reflexão mostram claramente os domínios dos solos argilosos e dos solos arenosos, com e sem a presença dos horizontes endurecidos.
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Kılıç, Alper, İsmail Babaoğlu, Ahmet Babalık, and Ahmet Arslan. "Through-Wall Radar Classification of Human Posture Using Convolutional Neural Networks." International Journal of Antennas and Propagation 2019 (March 31, 2019): 1–10. http://dx.doi.org/10.1155/2019/7541814.
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Through-wall detection and classification are highly desirable for surveillance, security, and military applications in areas that cannot be sensed using conventional measures. In the domain of these applications, a key challenge is an ability not only to sense the presence of individuals behind the wall but also to classify their actions and postures. Researchers have applied ultrawideband (UWB) radars to penetrate wall materials and make intelligent decisions about the contents of rooms and buildings. As a form of UWB radar, stepped frequency continuous wave (SFCW) radars have been preferred due to their advantages. On the other hand, the success of classification with deep learning methods in different problems is remarkable. Since the radar signals contain valuable information about the objects behind the wall, the use of deep learning techniques for classification purposes will give a different direction to the research. This paper focuses on the classification of the human posture behind the wall using through-wall radar signals and a convolutional neural network (CNN). The SFCW radar is used to collect radar signals reflected from the human target behind the wall. These signals are employed to classify the presence of the human and the human posture whether he/she is standing or sitting by using CNN. The proposed approach achieves remarkable and successful results without the need for detailed preprocessing operations and long-term data used in the traditional approaches.
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Shumeyko, A. E., and M. L. Yaskevich. "Ground penetrate radar test of a difficult nonhomogeneous stores." Environmental Protection in Oil and Gas Complex, no. 5 (2019): 42–50. http://dx.doi.org/10.33285/2411-7013-2019-5(290)-42-50.
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Xu, Qiangqiang, Jianquan Ge, and Tao Yang. "Optimal Design of Cooperative Penetration Trajectories for Multiaircraft." International Journal of Aerospace Engineering 2020 (January 25, 2020): 1–12. http://dx.doi.org/10.1155/2020/8490531.
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At present, two kinds of shortages exist in the research on cooperative combat. One is that radar detection threat (which cannot be ignored) is rarely considered. The other is that limited efforts have been made on the cooperative penetration trajectories under the conditions of long distance, vast airspace, and wide speed range. In order to offset the shortages of the research on cooperative combat, the penetration trajectory optimization method considering the influence of aircraft radar cross-section (RCS) and the cooperative penetration strategy is proposed in this study. Firstly, the RCS data are calculated by the physical optics (PO) method. The radar detection threat model is established considering the influence of the aircraft RCS. Then, a trajectory optimization framework with the dynamic model, constraint conditions, and optimal objectives is formed. Using the hp-adaptive Radau pseudospectral method, the optimal control problem for a single aircraft flight is solved. Finally, a cooperative penetration strategy is proposed to solve the cooperative penetration problem of multiaircraft. The impact time and angle constraints are given, and the virtual target point is introduced for terminal guidance. Two cases are simulated and verified. Simulation results demonstrate that the proposed method is effective. The single aircraft can effectively penetrate, and the multiaircraft can fulfill the requirement of cooperative impact time and angle under the condition of meeting the minimum threat of radar detection.
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El Hajj, Mohammad, Nicolas Baghdadi, Hassan Bazzi, and Mehrez Zribi. "Penetration Analysis of SAR Signals in the C and L Bands for Wheat, Maize, and Grasslands." Remote Sensing 11, no. 1 (December 26, 2018): 31. http://dx.doi.org/10.3390/rs11010031.
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This paper assesses the potential of Synthetic Aperture Radar (SAR) in the C and L bands to penetrate into the canopy cover of wheat, maize and grasslands. For wheat and grasslands, the sensitivity of the C and L bands to in situ surface soil moisture (SSM) was first studied according to three levels of the Normalized Difference Vegetation Index (NDVI < 0.4, 0.4 < NDVI < 0.7, and NDVI > 0.7). Next, the temporal evolution of the SAR signal in the C and L bands was analyzed according to SSM and the NDVI. For wheat and grasslands, the results showed that the L-band in HH polarization penetrates the canopy even when the canopy is well-developed (NDVI > 0.7), whereas the penetration of the C-band into the canopy is limited for an NDVI < 0.7. For an NDVI less than 0.7, the sensitivity of the radar signal to SSM is approximately 0.27 dB/vol.% for the L-band in HH polarization and approximately 0.12 dB/vol.% for the C-band (in both VV and VH polarizations). For highly developed wheat and grassland cover (NDVI > 0.7), the sensitivity of the L-band in HH polarization to SSM is approximately 0.19 dB/vol.%, whereas as the C-band is insensitive to SSM. For maize, only the temporal evolution of the C-band according to SSM and the NDVI was studied because the swath of SAR images in the L-band did not cover the maize plots. The results showed that the C-band in VV polarization is able to penetrate the maize canopy even when the canopy is well developed (NDVI > 0.7) due to high-order scattering along the soil-vegetation pathway that contains a soil contribution. According to results obtained in this paper, the L-band would penetrate a well-developed maize cover since the penetration depth of the L-band is greater than that of the C-band.
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Becker, K. F., L. Georgi, R. Kahle, S. Voges, F. Brandenburger, J. Höfer, C. Ehrhardt, et al. "Heterogeneous integration of a miniaturized W-band radar module." International Symposium on Microelectronics 2015, no. 1 (October 1, 2015): 000766–70. http://dx.doi.org/10.4071/isom-2015-thp11.
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For radar applications, the W-band frequency range (75 – 110 GHz) is a good candidate for high-resolution distance measurement and remote detection of small or hidden objects in distances of 10 cm to ≫ 20 m. As electromagnetic waves in this frequency range can easily penetrate rough atmosphere like fog, smoke or dust, W-band radars are perfectly suited for automotive, aviation, industrial and security applications. Additional benefit is that atmosphere has an absorption minimum at 94 GHz, so relative small output power is sufficient to achieve long range coverage. By combining and enhancing knowledge from the disciplines of heterogeneous integration technology and compound semiconductor-technology, the Fraunhofer Institutes IAF, IPA and IZM developed a miniaturized and low cost 94 GHz radar module. Result of this approach is a highly miniaturized radar module built using a modular approach. The radar components are mounted on a dedicated RF-NF-hybrid PCB while the signal processing is done on a separate board stacked below. This hybrid RF-module is combined with highly integrated digital processing PCB via micro connectors in a way that the radar system and an adapted conical HDPE-lens fit into an aluminum housing of 42×80×27 mm3 with a weight of only 160 grams for the whole module. The paper will describe the technological basis for such a frequency modulated continuous wave [FMCW] W-band radar module and describe in detail the technological features that enabled the assembly of such a miniaturized but high-performance system. The module yields an evaluated distance measurement accuracy of 5 ppm (5 μm deviation per meter target distance) while its low weight and small dimensions pave the way for a variety of new applications, including mobile operation.
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Hargrave, Chad, Lance Munday, Gareth Kennedy, and André de Kock. "Mine Machine Radar Sensor for Emergency Escape." Resources 9, no. 2 (February 4, 2020): 16. http://dx.doi.org/10.3390/resources9020016.
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This paper presents the results of recent work to develop and trial a mine machine radar sensor for underground coal mine vehicles. There is an urgent industry need for an integrated solution to the problem of operating an underground vehicle in conditions of dense ambient dust and/or smoke, such as may occur in underground coal mines after a fire or explosion. Under these conditions, sensors such as cameras and lidar offer limited assistance due to their inability to penetrate thick dust. Thermal infrared can penetrate dust but still results in poor vision, as there is insufficient temperature contrast between the tunnel walls and the ambient air. Microwave radar sensors are able to penetrate the dust, and suitable radar sensors have been developed for use in the automation industry. Adapting such sensors for use in an underground coal mining environment was the focus of this research effort, and involved trialing a suitable sensor in dust and smoke chambers as well as trials in an underground coal mine with introduced dust. Data processing and the development of a suitable user interface were key aspects of the research. Since any sensor would have to operate in an explosive atmosphere, a related research work developed a flameproof dielectric enclosure to allow the use of the radar in the mine environment.
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Jofre, L., A. Broquetas, J. Romeu, S. Blanch, A. P. Toda, X. Fabregas, and A. Cardama. "UWB Tomographic Radar Imaging of Penetrable and Impenetrable Objects." Proceedings of the IEEE 97, no. 2 (February 2009): 451–64. http://dx.doi.org/10.1109/jproc.2008.2008854.
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Hu, Xiaoyu, Jinming Ge, Jiajing Du, Qinghao Li, Jianping Huang, and Qiang Fu. "A robust low-level cloud and clutter discrimination method for ground-based millimeter-wavelength cloud radar." Atmospheric Measurement Techniques 14, no. 2 (March 3, 2021): 1743–59. http://dx.doi.org/10.5194/amt-14-1743-2021.
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Abstract. Low-level clouds play a key role in the energy budget and hydrological cycle of the climate system. The accurate long-term observation of low-level clouds is essential for understanding their climate effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their climate effect and the interaction with local abundant dust aerosol in semi-arid regions.
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Nag, S., and L. Peters. "Radar images of penetrable targets generated from ramp profile functions." IEEE Transactions on Antennas and Propagation 49, no. 1 (2001): 32–40. http://dx.doi.org/10.1109/8.910526.
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Holt, Benjamin, and F. D. Carsey. "The Separation of Sea-Ice Types in Radar Imagery (Abstract)." Annals of Glaciology 9 (1987): 247. http://dx.doi.org/10.3189/s0260305500000860.
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The ability to distinguish the several major types of sea ice with active radar instruments has been well studied in recent years. The separation of sea-ice types by radar results principally from variations in radar back-scatter due to characteristic differences of these ice types in surface morphology and brine content. When sea ice is viewed with an active radar at angles greater than about 20° from nadir, undeformed ice reflects radar waves and results in a low return, while ridges, hummocks, and small-scale surface features scatter the radar waves and produce a high return. The presence of salt increases the dielectric constant of ice; penetration by radar into the ice is then negligible, and the return is essentially determined by surface morphology. The absence of salt reduces the dielectric properties of ice; radar waves can then penetrate the ice to some depth and are scattered by air bubbles and brine-drainage channels (called volume scattering), thereby enhancing the return even for roughened surfaces. All these properties vary significantly with radar frequency and polarization as well as seasonally. For example, higher radar frequencies respond to smaller-scale surface features, while lower radar frequencies penetrate further into the ice with resulting volume scattering.The high-resolution imagery from synthetic aperture radars (SAR), mounted on aircraft, shuttle, or satellite platforms, is very effective for many sea-ice studies, including the separation of ice types. An aircraft-mounted X-band (9 GHz) SAR, for example, can discriminate smooth first-year ice, rough first-year ice, multi-year ice, and open water by the intensity (tone) of the radar returns and floe geometry. The preferred SARs to date for satellites and shuttle platforms have been L-band (1–2 GHz) systems. SAR imagery of sea ice was extensively acquired by Seasat in 1978 over the Beaufort Sea, with limited quantities obtained by the Shuttle Imaging Radar (SIR-B) over the Weddell Sea in 1984. While L-band SAR can discriminate rough and smooth ice along with roughened open water based on image intensity and floe geometry, the returns from thick first-year ice and multi-year ice are not clearly distinguishable. The fact that there is volume scattering from multi-year ice suggests that there may be textural or spatial frequency variations that could be used to separate these two major ice types in radar imagery. In order to investigate the separation of sea-ice types in the large amount of L-band SAR imagery available, image-analysis techniques including filtering and classification programs have been utilized, pointing towards an automatic classification algorithm for use in future SAR sea-ice data sets, especially from space.An important characteristic of all SAR imagery is the presence of image speckle, a coherent form of noise caused by the random variability of scatterers across even a uniform surface. Most SAR processors reduce this effect by averaging multiple independent samples but this is done at the cost of reducing resolution. Speckle reduction can also be accomplished by filtering. Several filters have been tested including median, box, and adaptive edge filters. Each filter has different characteristics in terms of smoothing speckle and in the response to sharp gradients or edges, such as ridge or lead openings, as well as computational requirements. Optimization of each filter’s parameters has been determined by the quality of classification of each ice type.The classification programs that have been tested are based on tone and texture image characteristics. The programs are supervised; that is, a small training area for each class is pre-selected for statistical analysis. From these statistics, the remainder of the imagery is subjected to the particular classification algorithm. The tone program separates classes based on the mean, standard deviation, and number of standard deviations of each class, and includes a Bayesian maximum-likelihood classifier for ambiguous elements. The texture program determines the statistical homogeneity of each class and the optimal segmentation of each small area into the various classes.
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Holt, Benjamin, and F. D. Carsey. "The Separation of Sea-Ice Types in Radar Imagery (Abstract)." Annals of Glaciology 9 (1987): 247. http://dx.doi.org/10.1017/s0260305500000860.
Full textAbstract:
The ability to distinguish the several major types of sea ice with active radar instruments has been well studied in recent years. The separation of sea-ice types by radar results principally from variations in radar back-scatter due to characteristic differences of these ice types in surface morphology and brine content. When sea ice is viewed with an active radar at angles greater than about 20° from nadir, undeformed ice reflects radar waves and results in a low return, while ridges, hummocks, and small-scale surface features scatter the radar waves and produce a high return. The presence of salt increases the dielectric constant of ice; penetration by radar into the ice is then negligible, and the return is essentially determined by surface morphology. The absence of salt reduces the dielectric properties of ice; radar waves can then penetrate the ice to some depth and are scattered by air bubbles and brine-drainage channels (called volume scattering), thereby enhancing the return even for roughened surfaces. All these properties vary significantly with radar frequency and polarization as well as seasonally. For example, higher radar frequencies respond to smaller-scale surface features, while lower radar frequencies penetrate further into the ice with resulting volume scattering. The high-resolution imagery from synthetic aperture radars (SAR), mounted on aircraft, shuttle, or satellite platforms, is very effective for many sea-ice studies, including the separation of ice types. An aircraft-mounted X-band (9 GHz) SAR, for example, can discriminate smooth first-year ice, rough first-year ice, multi-year ice, and open water by the intensity (tone) of the radar returns and floe geometry. The preferred SARs to date for satellites and shuttle platforms have been L-band (1–2 GHz) systems. SAR imagery of sea ice was extensively acquired by Seasat in 1978 over the Beaufort Sea, with limited quantities obtained by the Shuttle Imaging Radar (SIR-B) over the Weddell Sea in 1984. While L-band SAR can discriminate rough and smooth ice along with roughened open water based on image intensity and floe geometry, the returns from thick first-year ice and multi-year ice are not clearly distinguishable. The fact that there is volume scattering from multi-year ice suggests that there may be textural or spatial frequency variations that could be used to separate these two major ice types in radar imagery. In order to investigate the separation of sea-ice types in the large amount of L-band SAR imagery available, image-analysis techniques including filtering and classification programs have been utilized, pointing towards an automatic classification algorithm for use in future SAR sea-ice data sets, especially from space. An important characteristic of all SAR imagery is the presence of image speckle, a coherent form of noise caused by the random variability of scatterers across even a uniform surface. Most SAR processors reduce this effect by averaging multiple independent samples but this is done at the cost of reducing resolution. Speckle reduction can also be accomplished by filtering. Several filters have been tested including median, box, and adaptive edge filters. Each filter has different characteristics in terms of smoothing speckle and in the response to sharp gradients or edges, such as ridge or lead openings, as well as computational requirements. Optimization of each filter’s parameters has been determined by the quality of classification of each ice type. The classification programs that have been tested are based on tone and texture image characteristics. The programs are supervised; that is, a small training area for each class is pre-selected for statistical analysis. From these statistics, the remainder of the imagery is subjected to the particular classification algorithm. The tone program separates classes based on the mean, standard deviation, and number of standard deviations of each class, and includes a Bayesian maximum-likelihood classifier for ambiguous elements. The texture program determines the statistical homogeneity of each class and the optimal segmentation of each small area into the various classes.
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DE, A. C. "High Radar Clouds above 10 km." MAUSAM 14, no. 3 (March 4, 2022): 327–30. http://dx.doi.org/10.54302/mausam.v14i3.5462.
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Heights of tops of clouds above 10 km determined by the storm detecting radar at, Dum Dum airport during the premonsoon months (March-June) of 1961 have been verified on some occasions by means of post-flight reports from high-level flying aircrafts. Occasionally, the radar clouds have been found to penetrate the tropopause and lower stratosphere. Instanctes of such cases reported by radiometeorologists in other countries have also been mentioned.
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Scheffer, Louis K. "Investigating nearby exoplanets via interstellar radar." International Journal of Astrobiology 13, no. 1 (November 12, 2013): 62–68. http://dx.doi.org/10.1017/s147355041300030x.
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AbstractInterstellar radar is a potential intermediate step between passive observation of exoplanets and interstellar exploratory missions. Compared with passive observation, it has the traditional advantages of radar astronomy. It can measure surface characteristics, determine spin rates and axes, provide extremely accurate ranges, construct maps of planets, distinguish liquid from solid surfaces, find rings and moons, and penetrate clouds. It can do this even for planets close to the parent star. Compared with interstellar travel or probes, it also offers significant advantages. The technology required to build such a radar already exists, radar can return results within a human lifetime, and a single facility can investigate thousands of planetary systems. The cost, although too high for current implementation, is within the reach of Earth's economy.
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Songtao, Liu, Lei Zhenshuo, Ge Yang, and Wen Zhenming. "Automatic radar antenna scan type recognition based onlimited penetrable visibility graph." Journal of Systems Engineering and Electronics 32, no. 2 (April 2021): 437–46. http://dx.doi.org/10.23919/jsee.2021.000037.
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Mouginot, J., E. Rignot, Y. Gim, D. Kirchner, and E. Le Meur. "Low-frequency radar sounding of ice in East Antarctica and southern Greenland." Annals of Glaciology 55, no. 67 (2014): 138–46. http://dx.doi.org/10.3189/2014aog67a089.
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AbstractWe discuss a decameter-wavelength airborne radar sounder, the Warm Ice Sounding Explorer (WISE), that provides ice thickness in areas where radar signal penetration at higher frequencies is expected to be limited. Here we report results for three campaigns conducted in Greenland (2008, 2009, 2010) and two in Antarctica (2009, 2010). Comparisons with higher-frequency radar data indicate an accuracy of ±55 m for ice-thickness measurements in Greenland and ±25 m in Antarctica. We also estimate ice thickness of the Qassimiut lobe in southwest Greenland, where few ice-thickness measurements have been made, demonstrating that WISE penetrates in strongly scattering environments.
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Mallett, Robbie D. C., Isobel R. Lawrence, Julienne C. Stroeve, Jack C. Landy, and Michel Tsamados. "Brief communication: Conventional assumptions involving the speed of radar waves in snow introduce systematic underestimates to sea ice thickness and seasonal growth rate estimates." Cryosphere 14, no. 1 (January 27, 2020): 251–60. http://dx.doi.org/10.5194/tc-14-251-2020.
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Abstract. Pan-Arctic sea ice thickness has been monitored over recent decades by satellite radar altimeters such as CryoSat-2, which emits Ku-band radar waves that are assumed in publicly available sea ice thickness products to penetrate overlying snow and scatter from the ice–snow interface. Here we examine two expressions for the time delay caused by slower radar wave propagation through the snow layer and related assumptions concerning the time evolution of overlying snow density. Two conventional treatments introduce systematic underestimates of up to 15 cm into ice thickness estimates and up to 10 cm into thermodynamic growth rate estimates over multi-year ice in winter. Correcting these biases would impact a wide variety of model projections, calibrations, validations and reanalyses.
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Stumpf, Martin. "Radar Imaging of Impenetrable and Penetrable Targets From Finite-Duration Pulsed Signatures." IEEE Transactions on Antennas and Propagation 62, no. 6 (June 2014): 3035–42. http://dx.doi.org/10.1109/tap.2014.2309964.
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Chang, Pao-Liang, and Pin-Fang Lin. "Radar Anomalous Propagation Associated with Foehn Winds Induced by Typhoon Krosa (2007)." Journal of Applied Meteorology and Climatology 50, no. 7 (July 2011): 1527–42. http://dx.doi.org/10.1175/2011jamc2619.1.
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AbstractIn this study, unusual radar anomalous propagation (AP) phenomena associated with foehn winds induced by Typhoon Krosa (2007) were documented by using observations from radar, surface stations, and soundings. The AP echoes embedded within rainband areas and exhibited inward motions toward the radar site within 2–3 h prior to the occurrences of foehn winds at the radar site, which would interfere with the interpretation of radar data and associated downstream applications. As Typhoon Krosa appeared in the vicinity of the northeastern coast of Taiwan, foehn winds with significant subsidence warming and drying generated by downslope winds were observed in southeastern Taiwan. The foehn winds continuously moved northward within confined areas from the southeastern to eastern–central parts of Taiwan. Before the foehn winds penetrated to the surface, the subsidence warming introduced a temperature inversion layer above the surface and caused the ducting of radar beams. Analyses of refractive index and ray tracing suggested that the occurrence and evolution of the AP echoes during Typhoon Krosa were closely related to the varying inversion heights induced by downslope winds.
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Rizaldy, Aldino, and Ratna Mayasari. "ACCELERATION OF TOPOGRAPHIC MAP PRODUCTION USING SEMI-AUTOMATIC DTM FROM DSM RADAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 47–54. http://dx.doi.org/10.5194/isprs-archives-xli-b7-47-2016.
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Badan Informasi Geospasial (BIG) is government institution in Indonesia which is responsible to provide Topographic Map at several map scale. For medium map scale, e.g. 1:25.000 or 1:50.000, DSM from Radar data is very good solution since Radar is able to penetrate cloud that usually covering tropical area in Indonesia. DSM Radar is produced using Radargrammetry and Interferrometry technique. The conventional method of DTM production is using “stereo-mate”, the stereo image created from DSM Radar and ORRI (Ortho Rectified Radar Image), and human operator will digitizing masspoint and breakline manually using digital stereoplotter workstation. This technique is accurate but very costly and time consuming, also needs large resource of human operator. Since DSMs are already generated, it is possible to filter DSM to DTM using several techniques. This paper will study the possibility of DSM to DTM filtering using technique that usually used in point cloud LIDAR filtering. Accuracy of this method will also be calculated using enough numbers of check points. If the accuracy meets the requirement, this method is very potential to accelerate the production of Topographic Map in Indonesia.
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Pei, Yang, Qiang Dong, Ting Guo, and Bi Feng Song. "Automotive Route Planning Method for Minimizing the Radar Detection of an Armed Helicopter." Applied Mechanics and Materials 55-57 (May 2011): 1541–46. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.1541.
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Radar systems are used by air defense forces to detect and track aircraft. Route planning attempts to enhance safety by minimizing the exposure of the aircraft to the threat air defense systems while achieving the mission objectives. Based on Voronoi diagram theory, a flight route optimization method is introduced to insure the armed helicopter to penetrate the emery’s radar defense system at the lowest danger. The factors, such as radar cross section and distance between helicopter and radar, that affect the radar detection are firstly analyzed. Then Voronoi diagram and its application for route planning to minimize the detection probability of an armed helicopter are described introduced in details. Dijkstra algorithm is employed to solve the optimization problem and to obtain the initial flight path. The simulation of artificial potential field dynamic is performed to transform the initial path to the smooth flight route. Example analysis of a hypothesis armed helicopter shows that the developed method is helpful for the on-the-spot planning that combines aircraft flight performance and intelligence information regarding the estimated enemy weapon locations to develop routes that avoid or mask the enemy sensor and weapon envelopes.
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Rizaldy, Aldino, and Ratna Mayasari. "ACCELERATION OF TOPOGRAPHIC MAP PRODUCTION USING SEMI-AUTOMATIC DTM FROM DSM RADAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 47–54. http://dx.doi.org/10.5194/isprsarchives-xli-b7-47-2016.
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Badan Informasi Geospasial (BIG) is government institution in Indonesia which is responsible to provide Topographic Map at several map scale. For medium map scale, e.g. 1:25.000 or 1:50.000, DSM from Radar data is very good solution since Radar is able to penetrate cloud that usually covering tropical area in Indonesia. DSM Radar is produced using Radargrammetry and Interferrometry technique. The conventional method of DTM production is using “stereo-mate”, the stereo image created from DSM Radar and ORRI (Ortho Rectified Radar Image), and human operator will digitizing masspoint and breakline manually using digital stereoplotter workstation. This technique is accurate but very costly and time consuming, also needs large resource of human operator. Since DSMs are already generated, it is possible to filter DSM to DTM using several techniques. This paper will study the possibility of DSM to DTM filtering using technique that usually used in point cloud LIDAR filtering. Accuracy of this method will also be calculated using enough numbers of check points. If the accuracy meets the requirement, this method is very potential to accelerate the production of Topographic Map in Indonesia.
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Yoo, Wang, Seol, Lee, Chung, and Cho. "A Multiple Target Positioning and Tracking System Behind Brick-Concrete Walls Using Multiple Monostatic IR-UWB Radars." Sensors 19, no. 18 (September 18, 2019): 4033. http://dx.doi.org/10.3390/s19184033.
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Recognizing and tracking the targets located behind walls through impulse radio ultra-wideband (IR-UWB) radar provides a significant advantage, as the characteristics of the IR-UWB radar signal enable it to penetrate obstacles. In this study, we design a through-wall radar system to estimate and track multiple targets behind a wall. The radar signal received through the wall experiences distortion, such as attenuation and delay, and the characteristics of the wall are estimated to compensate the distance error. In addition, unlike general cases, it is difficult to maintain a high detection rate and low false alarm rate in this through-wall radar application due to the attenuation and distortion caused by the wall. In particular, the generally used delay-and-sum algorithm is significantly affected by the motion of targets and distortion caused by the wall, rendering it difficult to obtain a good performance. Thus, we propose a novel method, which calculates the likelihood that a target exists in a certain location through a detection process. Unlike the delay-and-sum algorithm, this method does not use the radar signal directly. Simulations and experiments are conducted in different cases to show the validity of our through-wall radar system. The results obtained by using the proposed algorithm as well as delay-and-sum and trilateration are compared in terms of the detection rate, false alarm rate, and positioning error.
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Tang, X., S. Cheng, and J. Guo. "NOISE REDUCTION AND INTERPRETATION OF ICE-PENETRATING RADAR DATA IN ANTARCTIC ICE SHEET BASED ON VARIATIONAL MODE DECOMPOSITION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 1787–91. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-1787-2019.
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<p><strong>Abstract.</strong> Ice-penetrating radar is an effective method for studying the subglacial bedrock and ice information within the Antarctic ice sheet. Because of the low conductivity of ice and the relatively uniform composition of ice sheets in the polar region, ice-penetrating radar can penetrate deeper part of the ice sheet and collect the following data. However, it is still necessary to suppress the noise from radar data to obtain more accurate and effective data. In this paper, the entirely non-recursive Variational Mode Decomposition (VMD) is applied to the data noise reduction of ice-penetrating radar data. VMD is a decomposition method of adaptive and quasi-orthogonal signals, which decomposes airborne radar data into multiple frequency-limited quasi-orthogonal Intrinsic Mode Functions (IMFs). The IMFs containing noise are then removed according to the information distribution in the IMFs component and the remaining IMFs are reconstructed. We implements the method to process the real ice-penetrating radar data, which effectively eliminates the interference noise in the data, improves the signal-to-noise ratio and characterizes the internal layer structure of ice. It is verified that the method can be applied to the noise reduction processing of polar ice-penetrating radar data successful, which provides a better basis for data interpretation. Finally, we present the internal structure within the ice sheet based on VMD denoised radar profile.</p>
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Almutiry, M. "UAV Tomographic Synthetic Aperture Radar for Landmine Detection." Engineering, Technology & Applied Science Research 10, no. 4 (August 16, 2020): 5933–39. http://dx.doi.org/10.48084/etasr.3611.
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The development of the Unmanned Aerial Vehicle (UAV) and communication systems contributed to the availability of more applications using UAVs in military and civilians purposes. Anti-personnel landmines deployed by militia groups in conflict zones are a life threat for civilians and need cautious handling while removing. The UAV Tomographic Synthetic Aperture Radar (TSAR) can reconstruct three-dimension images of the investigation domain to prescreen nonmetallic landmines. A nonmetallic landmine cannot be detected using conventional ground penetrating radars when the scattering field is undetected due to the dielectric permittivity. In this paper, imaging the underground for detecting landmine using TSAR is proposed. The TSAR has the capability of prosing the data in discrete mode regardless of the altitude of UAV’s radar. A landmine is always buried less than a feet depth. L-band frequency is used to provide high resolution and to penetrate deep in dry soil. More than one UAVs are used to multistatic scan the investigation space. The geometric diversity of multistatic distribution of the sensors will provide more information about the buried nonmetallic landmines, certain features, and their location. The data collected from the sensors will align with the geolocation data obtained from the UAV’s system for processing. Dynamic flying can be used to predict the electromagnetic response of the scattering field to create a dynamic matching filter using the Green’s function under first-order Born approximation. The occurring air-soil interference has been removed as an unwanted reflection from the ground while keeping the signal coming from underground. Using the Born approximation assumption created an ill-posed linear system solved by the Conjugate Gradient algorithm. Simulation results are presented to validate the method.
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Liu, Feng, Quan Shi, Guang Yan Wang, and Bao Quan Zhang. "Simulation on the Planar Array Antenna Penetrated to Tungsten Spherical Fragment." Advanced Materials Research 753-755 (August 2013): 1060–64. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.1060.
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Assess the array element number of planar phased array antenna which suffers fragments combat damage. A single fragment damage as the research object, the simulation of penetration condition for Tungsten Spherical fragments is developed using the software of ANSYS/LS-DYNA. The penetration of antenna at 0°attack angel and 800m/s is simulated, and we can gain the penetrated distortion data. Based on the data the damage circular is calculated. The last one study was made on x-band planar array antennas, the array elements invulnerability of triangular setting is better than rectangular, and the influence characteristics between the position of the damage circle and the damage of the antenna. The results can be used in a rapid assessment of a battle-damaged Radar repair and maintain inventory of phased-Array element.
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KULSHRESTHA, SM, and PS JAIN. "Radar-Climatology of Delhi and neighbourhood: Occurrence of severe weather." MAUSAM 18, no. 1 (April 30, 2022): 105–10. http://dx.doi.org/10.54302/mausam.v18i1.4009.
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Occurrence of severe weather, observed within a range of 200 miles around Delhi, has been investigated with reference to the maximum heights of echo tops reported in the area. While the number of severe weather reports increases with the increase in maximum heights of echo tops in the area, no significant increase in severe weather activity is observed when the echo tops reach or penetrate the tropopause. The monthly distribution of the number of hail occurrences as well as their preferred hours of occurrence have also been studied for the region.
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Junior, Milembolo Miantezila, and Bin Guo. "Sensing spectrum sharing based massive MIMO radar for drone tracking and interception." PLOS ONE 17, no. 5 (May 20, 2022): e0268834. http://dx.doi.org/10.1371/journal.pone.0268834.
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Radar sensors are becoming crucial for environmental perception in a world with the tremendous growth of unmanned aerial vehicles (UAVs) or drones. When public safety is a concern, the localization of drones are of great significance. However, a drone used for a wrong motive can cause a serious problem for the environment and public safety, given the fact that the dynamic movement of a drone’s emission signal and location tracking is different from existing positioning. This study proposes a safety zone characterized by the presence of N radars sensors with a goal to track and destabilized rogue drones attending to penetrate safety zones (stadium and school). Specifically, a new joint estimation based on a Gaussian filter has been introduced for spectrum sharing and detection awareness. The profit of this novel sensing method can be clearly seen when the two joint hidden states are taken into consideration. Therefore, the drone’s emission state is analyzed by estimating its movement jointly. Considering the drone’s unknown states and actual positioning, an algorithm is developed based on dynamic states space model. Where Bernoulli filter model is designed to estimate recursively the unknown stages of the drone and its changing location based on time. Meanwhile a power control acted from the radar to the targeted drones so that rogue drones are optimally tracked and destabilized over time. Furthermore, an expanding mechanism has been generated to accurately track the drone and enhance detection. A thoughtful result of the experimentation shows clearly that, even when the drone is moving, spectral detection can be performed accurately by chasing its positions. Its demonstrates at 90% of credibility that the original signal has a direct effect on the propagated signal. Therefore, the magnitude of the Doppler shift increases with frequency. And the clue of its positioning can be used for cognitive radio optimization.
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Tonboe, R. T., L. T. Pedersen, and C. Haas. "Simulation of the satellite radar altimeter sea ice thickness retrieval uncertainty." Cryosphere Discussions 3, no. 2 (July 21, 2009): 513–59. http://dx.doi.org/10.5194/tcd-3-513-2009.
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Abstract. Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009) satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea) the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.
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POLIDORI, Laurent, Carlos Rodrigo Tanajura CALDEIRA, Maël SMESSAERT, and Mhamad EL HAGE. "Digital elevation modeling through forests: the challenge of the Amazon." Acta Amazonica 52, no. 1 (January 2022): 69–80. http://dx.doi.org/10.1590/1809-4392202103091.
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ABSTRACT Elevation mapping at ground level is challenging in forested areas like the Amazon region, which is mostly covered by dense rainforest. The most common techniques, i.e. photogrammetry and short wavelength radar, provide elevations at canopy level at best, while most applications require ground elevations. Even lidar and P-band radar, which can penetrate foliage and measure elevations at ground level, have some limitations which are analyzed in here. We address three research questions: To what extent can a terrain model be replaced by a more easily available canopy-level surface model for topography-based applications? How can the elevation be obtained at ground level through forest? Can a priori knowledge of general continental relief properties be used to compensate for the limits of measurement methods in the presence of forest?
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Hosseiny, B., N. Ghasemian, and J. Amini. "A CONVOLUTIONAL NEURAL NETWORK FOR FLOOD MAPPING USING SENTINEL-1 AND SRTM DEM DATA: CASE STUDY IN POLDOKHTAR-IRAN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 527–33. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-527-2019.
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Abstract. Flood contributes a key role in devastating natural and man-made areas. Floods usually are occurred when there is a considerable number of clouds in the sky making optic data useless. Synthetic aperture radar (SAR) images can be a valuable data source in earth observation tasks. The most important characteristic of the radar image is its ability to penetrate the cloud and dust. Therefore, monitoring earth in cloudy or rainy weather can be available by this kind of dataset. In the last few years by improving machine learning methods and development of convolutional neural networks in remote sensing applications we are facing with extremely high improvement in classification tasks. In this paper, we use dual-polarized VV and VH backscatter values of Sentinel-1 and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) dataset in a proposed convolutional neural network to generate a land cover map of a flooded area before and after happening. Obtained classification results vary between 93.3% to 98.5% for different training sizes. By comparing the generated classified maps, flooded areas of each class can be extracted.
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Munthe, CR, and N. Sulistiyono. "Above Ground Carbon Estimation Using Sentinel-1B RADAR Satellite Imagery." Journal of Physics: Conference Series 2421, no. 1 (January 1, 2023): 012037. http://dx.doi.org/10.1088/1742-6596/2421/1/012037.
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Abstract Mangroves are an important forest ecosystem in Indonesia because mangroves are known to have the ability to store high carbon. The use of remote sensing technology can be used to estimate the distribution of carbon content. The advantage of using radar satellite imagery such as Sentinel-1b is its ability to penetrate clouds. Satellite images produced from radar satellites are cloud-free satellite images. The purpose of this study was to obtain information on the spatial distribution of above-ground carbon (AGC) using the Sentinel-1b radar satellite imagery in the Karang Gading dan Langkat Timur Laut Wildlife Reserve. Regression is used to estimate the distribution of AGC based on the backscattering values of VH, VV, VV/VH, VV-VH, and VV+VH. The results showed that the carbon distribution in the best model was 45.02 tons ha-1 to 222.16 tons ha-1. The quadratic regression model with VV-VH backscatter is the best model for estimating AGC with a value of R2 = 0.374, and the value of Root Mean Square Error (RMSE) value of 19.083 ha/ton.
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Orosei, Roberto, Chunyu Ding, Wenzhe Fa, Antonios Giannopoulos, Alain Hérique, Wlodek Kofman, Sebastian E. Lauro, et al. "The Global Search for Liquid Water on Mars from Orbit: Current and Future Perspectives." Life 10, no. 8 (July 24, 2020): 120. http://dx.doi.org/10.3390/life10080120.
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Due to its significance in astrobiology, assessing the amount and state of liquid water present on Mars today has become one of the drivers of its exploration. Subglacial water was identified by the Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) aboard the European Space Agency spacecraft Mars Express through the analysis of echoes, coming from a depth of about 1.5 km, which were stronger than surface echoes. The cause of this anomalous characteristic is the high relative permittivity of water-bearing materials, resulting in a high reflection coefficient. A determining factor in the occurrence of such strong echoes is the low attenuation of the MARSIS radar pulse in cold water ice, the main constituent of the Martian polar caps. The present analysis clarifies that the conditions causing exceptionally strong subsurface echoes occur solely in the Martian polar caps, and that the detection of subsurface water under a predominantly rocky surface layer using radar sounding will require thorough electromagnetic modeling, complicated by the lack of knowledge of many subsurface physical parameters. Higher-frequency radar sounders such as SHARAD cannot penetrate deep enough to detect basal echoes over the thickest part of the polar caps. Alternative methods such as rover-borne Ground Penetrating Radar and time-domain electromagnetic sounding are not capable of providing global coverage. MARSIS observations over the Martian polar caps have been limited by the need to downlink data before on-board processing, but their number will increase in coming years. The Chinese mission to Mars that is to be launched in 2020, Tianwen-1, will carry a subsurface sounding radar operating at frequencies that are close to those of MARSIS, and the expected signal-to-noise ratio of subsurface detection will likely be sufficient for identifying anomalously bright subsurface reflectors. The search for subsurface water through radar sounding is thus far from being concluded.
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Bindschadler, R. A., K. C. Jezek, and J. Crawford. "Glaciological Investigations Using the Synthetic Aperture Radar Imaging System." Annals of Glaciology 9 (1987): 11–19. http://dx.doi.org/10.3189/s0260305500200694.
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Numerous examples of synthetic aperture radar (SAR) imagery of ice sheets are shown and prominent features of glaciological importance which appear in the images are discussed. Features which can be identified include surface undulations, ice-flow lines, crevasses, icebergs, lakes, and streams (even lakes and streams which are inactive or covered by snow), and possibly, the extent of the ablation and wet snow zones. SAR images presented here include both L-band data from the Seasat satellite and X-band data from an airborne radar. These two data sets overlap at a part of eastern Greenland where a direct comparison can be made between two images. Comparison is also made between SAR and Landsat images in western Greenland. It is concluded that SAR and Landsat are highly complementary instruments; Landsat images contain minimal distortion while SAR’s all-weather, day/night capability plus its ability to penetrate snow provide glaciologists with an additional and very powerful tool for research.
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Bindschadler, R. A., K. C. Jezek, and J. Crawford. "Glaciological Investigations Using the Synthetic Aperture Radar Imaging System." Annals of Glaciology 9 (1987): 11–19. http://dx.doi.org/10.1017/s0260305500000318.
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Numerous examples of synthetic aperture radar (SAR) imagery of ice sheets are shown and prominent features of glaciological importance which appear in the images are discussed. Features which can be identified include surface undulations, ice-flow lines, crevasses, icebergs, lakes, and streams (even lakes and streams which are inactive or covered by snow), and possibly, the extent of the ablation and wet snow zones. SAR images presented here include both L-band data from the Seasat satellite and X-band data from an airborne radar. These two data sets overlap at a part of eastern Greenland where a direct comparison can be made between two images. Comparison is also made between SAR and Landsat images in western Greenland. It is concluded that SAR and Landsat are highly complementary instruments; Landsat images contain minimal distortion while SAR’s all-weather, day/night capability plus its ability to penetrate snow provide glaciologists with an additional and very powerful tool for research.
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Bindschadler, R. A., K. C. Jezek, and J. Crawford. "Glaciological Investigations Using the Synthetic Aperture Radar Imaging System." Annals of Glaciology 9 (1987): 11–19. http://dx.doi.org/10.1017/s0260305500200694.
Full textAbstract:
Numerous examples of synthetic aperture radar (SAR) imagery of ice sheets are shown and prominent features of glaciological importance which appear in the images are discussed. Features which can be identified include surface undulations, ice-flow lines, crevasses, icebergs, lakes, and streams (even lakes and streams which are inactive or covered by snow), and possibly, the extent of the ablation and wet snow zones. SAR images presented here include both L-band data from the Seasat satellite and X-band data from an airborne radar. These two data sets overlap at a part of eastern Greenland where a direct comparison can be made between two images. Comparison is also made between SAR and Landsat images in western Greenland. It is concluded that SAR and Landsat are highly complementary instruments; Landsat images contain minimal distortion while SAR’s all-weather, day/night capability plus its ability to penetrate snow provide glaciologists with an additional and very powerful tool for research.
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Mahmud, Nurush Syamimie, S. A. Abdul Shukor, H. Ali, A. F. Ahmad Zaidi, M. S. Zanar Azalan, T. S. Tengku Amran, and M. R. Ahmad. "Underground object reconstruction from Ground Penetrating Radar (GPR) data – An investigative study of feature extraction." Journal of Physics: Conference Series 2107, no. 1 (November 1, 2021): 012062. http://dx.doi.org/10.1088/1742-6596/2107/1/012062.
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Abstract Ground Penetrating Radar (GPR) is very useful for underground object detection as its signal able to penetrate surfaces in obtaining the underneath information. However, its radargram output in hyperbolic signal are very challenging to be analyzed. This work investigates the suitability of selected data processing methods in extracting important features of the signal in order to understand and reconstruct it to make it more beneficial. Results show that with suitable combination of data processing, it able to extract the peak of the hyperbolic signal accordingly and further reconstruction can be made.
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Tsibizov, L. V., E. I. Esin, A. V. Grigorevskaya, and K. A. Sosnovtsev. "Magnetometry and ground penetrating radar in application to mapping of polygonal wedge ice of yedoma complex." Arctic and Antarctic Research 64, no. 4 (December 26, 2018): 427–38. http://dx.doi.org/10.30758/0555-2648-2018-64-4-427-438.
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Paper is dedicated to geophysical mapping of polygonal wedge ice. Magnetometric and ground penetrating radar surveys were implemented on a small area of Yedoma ice complex on Kurungnakh island in Lena river delta. Such deposits are widely spread on a huge areas of Siberia and Alaska. The study was conducted near the thermoerosional gully, which propagates along the most thick ice wedges. Polygonal pattern is observable on high-resolution aerial imagery and digital elevation model - this data was used during the interpreting of obtained results. Study area (40×50 m) was covered with highresolution magnetic survey at the elevation of 2 m with 2×2 m step and with ground penetrating radar survey along profiles with 1 m distance between the profiles. Map of total magnetic field anomalies allow to determine the ice wedges of Yedoma ice complex distinctly. Difference between maximum positive (polygons centers) and negative (ice wedges) anomalies reaches 6 nT (error of the survey is 0,3 nT). Beyond that smaller ice wedges which penetrate the ice wedges of Yedoma complex are also observable in magnetic field. Basing on ground penetrating radar data an amplitude slice of at 3,5 m depth was built. Yedoma ice wedges are observable at depth of 3–4 m. Ground penetrating radar data is quite noisy due to surface inhomogeneity (puddles, knolls, etc.). Results of the surveys were compared in the light of practical application of the methods for above mentioned goal. Magnetometric method appears as more efficient than ground penetrating radar survey: it does not require a contact with the surface and more rapid, it is more sensitive as the case stands. Ground penetrating radar method may have advantages in the case of natural (magnetic storm, high-magnetized overlaying deposits) and anthropogenic (metal constructions — pipelines, ETL) noise.
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Souza, Priscila E., Aart Kroon, and Lars Nielsen. "Beach-ridge architecture constrained by beach topography and ground-penetrating radar, Itilleq (Laksebugt), south-west Disko, Greenland – implications for sea-level reconstructions." Bulletin of the Geological Society of Denmark 66 (September 7, 2018): 167–79. http://dx.doi.org/10.37570/bgsd-2018-66-08.
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Detailed topographic data and high-resolution ground-penetrating radar (GPR) reflection data are presented from the present-day beach and across successive raised beach ridges at Itilleq, south-west Disko, West Greenland. In the western part of the study area, the present low-tide level is well defined by an abrupt change in sediment grain size between the sandy foreshore and the upper shoreface that is characterised by frequently occurring large clasts. The main parts of both fine and large clasts appear to be locally derived. Seaward-dipping reflections form downlap points, which are clearly identified in all beach-ridge GPR profiles. Most of them are located at the boundary between a unit with reflection characteristics representing palaeo-foreshore deposits and a deeper and more complex radar unit characterised by diffractions; the deeper unit is not penetrated to large depths by the GPR signals. Based on observations of the active shoreface regime, large clasts are interpreted to give rise to scattering observed near the top of the deeper radar unit. We regard the downlap points located at this radar boundary as markers of palaeo-low-tide levels. In some places, scattering hyperbolas are more pronounced and frequent than in others, suggesting differences in the occurrence of large boulders.
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Zhao, J., and D. Floricioiu. "THE PENETRATION EFFECTS ON TANDEM-X ELEVATION USING THE GNSS AND LASER ALTIMETRY MEASUREMENTS IN ANTARCTICA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 14, 2017): 1593–600. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-1593-2017.
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Synthetic Aperture Radar (SAR) has been widely used in many different fields, such as geoscience, climate monitoring, security-related applications. However, over natural terrain the radar signal has the ability to penetrate the ground surface which can cause the bias in the elevation measurements. The aim of the paper is to assess the SAR signal penetration effect on the TanDEM-X absolute elevation over ice and snow covered areas and it presents the results concerning the X-band SAR signal penetration effect on dry snow areas and blue ice region. Additionally, the relationship between SAR signal penetration depth and backscattering coefficient is exploited and discussed. In this paper, two study sites, Schirmacher area and Recovery Ice Stream are selected and it is found that the general X-band SAR signal penetration depth is around 3&ndash;7 meter on dry snow area while no penetration depth is expected on the blue-ice region.
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Ranjan, Yatharth, Zulqarnain Rashid, Callum Stewart, Pauline Conde, Mark Begale, Denny Verbeeck, Sebastian Boettcher, Richard Dobson, and Amos Folarin. "RADAR-Base: Open Source Mobile Health Platform for Collecting, Monitoring, and Analyzing Data Using Sensors, Wearables, and Mobile Devices." JMIR mHealth and uHealth 7, no. 8 (August 1, 2019): e11734. http://dx.doi.org/10.2196/11734.
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Background With a wide range of use cases in both research and clinical domains, collecting continuous mobile health (mHealth) streaming data from multiple sources in a secure, highly scalable, and extensible platform is of high interest to the open source mHealth community. The European Union Innovative Medicines Initiative Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) program is an exemplary project with the requirements to support the collection of high-resolution data at scale; as such, the Remote Assessment of Disease and Relapse (RADAR)-base platform is designed to meet these needs and additionally facilitate a new generation of mHealth projects in this nascent field. Objective Wide-bandwidth networks, smartphone penetrance, and wearable sensors offer new possibilities for collecting near-real-time high-resolution datasets from large numbers of participants. The aim of this study was to build a platform that would cater for large-scale data collection for remote monitoring initiatives. Key criteria are around scalability, extensibility, security, and privacy. Methods RADAR-base is developed as a modular application; the backend is built on a backbone of the highly successful Confluent/Apache Kafka framework for streaming data. To facilitate scaling and ease of deployment, we use Docker containers to package the components of the platform. RADAR-base provides 2 main mobile apps for data collection, a Passive App and an Active App. Other third-Party Apps and sensors are easily integrated into the platform. Management user interfaces to support data collection and enrolment are also provided. Results General principles of the platform components and design of RADAR-base are presented here, with examples of the types of data currently being collected from devices used in RADAR-CNS projects: Multiple Sclerosis, Epilepsy, and Depression cohorts. Conclusions RADAR-base is a fully functional, remote data collection platform built around Confluent/Apache Kafka and provides off-the-shelf components for projects interested in collecting mHealth datasets at scale.
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Schimmel, Willi, Heike Kalesse-Los, Maximilian Maahn, Teresa Vogl, Andreas Foth, Pablo Saavedra Garfias, and Patric Seifert. "Identifying cloud droplets beyond lidar attenuation from vertically pointing cloud radar observations using artificial neural networks." Atmospheric Measurement Techniques 15, no. 18 (September 21, 2022): 5343–66. http://dx.doi.org/10.5194/amt-15-5343-2022.
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Abstract. In mixed-phase clouds, the variable mass ratio between liquid water and ice as well as the spatial distribution within the cloud plays an important role in cloud lifetime, precipitation processes, and the radiation budget. Data sets of vertically pointing Doppler cloud radars and lidars provide insights into cloud properties at high temporal and spatial resolution. Cloud radars are able to penetrate multiple liquid layers and can potentially be used to expand the identification of cloud phase to the entire vertical column beyond the lidar signal attenuation height, by exploiting morphological features in cloud radar Doppler spectra that relate to the existence of supercooled liquid. We present VOODOO (reVealing supercOOled liquiD beyOnd lidar attenuatiOn), a retrieval based on deep convolutional neural networks (CNNs) mapping radar Doppler spectra to the probability of the presence of cloud droplets (CD). The training of the CNN was realized using the Cloudnet processing suite as supervisor. Once trained, VOODOO yields the probability for CD directly at Cloudnet grid resolution. Long-term predictions of 18 months in total from two mid-latitudinal locations, i.e., Punta Arenas, Chile (53.1∘ S, 70.9∘ W), in the Southern Hemisphere and Leipzig, Germany (51.3∘ N, 12.4∘ E), in the Northern Hemisphere, are evaluated. Temporal and spatial agreement in cloud-droplet-bearing pixels is found for the Cloudnet classification to the VOODOO prediction. Two suitable case studies were selected, where stratiform, multi-layer, and deep mixed-phase clouds were observed. Performance analysis of VOODOO via classification-evaluating metrics reveals precision > 0.7, recall ≈ 0.7, and accuracy ≈ 0.8. Additionally, independent measurements of liquid water path (LWP) retrieved by a collocated microwave radiometer (MWR) are correlated to the adiabatic LWP, which is estimated using the temporal and spatial locations of cloud droplets from VOODOO and Cloudnet in connection with a cloud parcel model. This comparison resulted in stronger correlation for VOODOO (≈ 0.45) compared to Cloudnet (≈ 0.22) and indicates the availability of VOODOO to identify CD beyond lidar attenuation. Furthermore, the long-term statistics for 18 months of observations are presented, analyzing the performance as a function of MWR–LWP and confirming VOODOO's ability to identify cloud droplets reliably for clouds with LWP > 100 g m−2. The influence of turbulence on the predictive performance of VOODOO was also analyzed and found to be minor. A synergy of the novel approach VOODOO and Cloudnet would complement each other perfectly and is planned to be incorporated into the Cloudnet algorithm chain in the near future.
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Yue, Zhang. "We are Telling the World Everything the Cerebral Cortex Memorises." Britain International of Exact Sciences (BIoEx) Journal 2, no. 2 (May 8, 2020): 486–88. http://dx.doi.org/10.33258/bioex.v2i2.224.
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The cognitions and thoughts of a human brain are accomplished by the neurons to transmit informations in brain. If we want to know the thoughts of a brain, we must to contact the neural network of the brain. One of the well-known way is to penetrate the capillary holes of the surface of the brain with electromagnetic waves to contact neurons. The modern method is to emit electromagnetic waves with radar via the GPS which can make lights exactly and easily pass through the capillary holes of the brain.The paper will simply describe the principle of their works.
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Zhou, Feng, Iraklis Giannakis, Antonios Giannopoulos, Klaus Holliger, and Evert Slob. "Estimating reservoir permeability with borehole radar." GEOPHYSICS 85, no. 4 (June 10, 2020): H51—H60. http://dx.doi.org/10.1190/geo2019-0696.1.
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In oil drilling, mud filtrate penetrates into porous formations and alters the compositions and properties of the pore fluids. This disturbs the logging signals and brings errors to reservoir evaluation. Drilling and logging engineers therefore deem mud invasion as undesired and attempt to eliminate its adverse effects. However, the mud-contaminated formation carries valuable information, notably with regard to its hydraulic properties. Typically, the invasion depth critically depends on the formation porosity and permeability. Therefore, if adequately characterized, mud invasion effects could be used for reservoir evaluation. To pursue this objective, we have applied borehole radar to measure mud invasion depth considering its high radial spatial resolution compared with conventional logging tools, which then allows us to estimate the reservoir permeability based on the acquired invasion depth. We investigate the feasibility of this strategy numerically through coupled electromagnetic and fluid modeling in an oil-bearing layer drilled using freshwater-based mud. Time-lapse logging is simulated to extract the signals reflected from the invasion front, and a dual-offset downhole antenna mode enables time-to-depth conversion to determine the invasion depth. Based on drilling, coring, and logging data, a quantitative interpretation chart is established, mapping the porosity, permeability, and initial water saturation into the invasion depth. The estimated permeability is in a good agreement with the actual formation permeability. Our results therefore suggest that borehole radar has significant potential to estimate permeability through mud invasion effects.
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Huang, K. M., A. Z. Liu, S. D. Zhang, F. Yi, C. M. Huang, Q. Gan, Y. Gong, Y. H. Zhang, and R. Wang. "Observational evidence of quasi-27-day oscillation propagating from the lower atmosphere to the mesosphere over 20° N." Annales Geophysicae 33, no. 10 (October 30, 2015): 1321–30. http://dx.doi.org/10.5194/angeo-33-1321-2015.
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Abstract. By using meteor radar, radiosonde and satellite observations over 20° N and NCEP/NCAR reanalysis data during 81 days from 22 December 2004 to 12 March 2005, a quasi-27-day oscillation propagating from the troposphere to the mesosphere is reported. A pronounced 27-day periodicity is observed in the raw zonal wind from meteor radar. Spectral analysis shows that the oscillation also occurs in the meridional wind and temperature and propagates westward with wavenumber s = 1; thus the oscillation is of Rossby wave type. The oscillation attains a large amplitude of about 12 m s−1 in the eastward wind shear region of the troposphere. When the wind shear reverses, its amplitude rapidly decays, and the background wind gradually evolves to be westward. However, the oscillation can penetrate through the weak westward wind field due to its relatively large phase speed. After this, the oscillation restrengthens with its upward propagation and reaches about 20 m s−1 in the mesosphere. Reanalysis data show that the oscillation can propagate to the mid and high latitudes from the low latitudes and has large amplitudes over there. There is another interesting phenomenon that a quasi-46-day oscillation appears simultaneously in the troposphere, but it cannot penetrate through the westward wind field because of its smaller phase speed. In the observational interval, a quasi-27-day periodicity in outgoing long-wave radiation (OLR) and specific humidity is found in a latitudinal zone of 5–20° N. Thus the quasi-27-day oscillation may be an atmospheric response to forcing due to the convective activity with a period of about 27 days in the tropical region.
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Choudhury, Aloshree, Dr Vazeer Mahammood, and Dr K. H. V. Durga Rao. "Rice Mapping and Various Stages of Rice Growth using Sentinel-1 SAR Data-A case study of Mahabubnagar District, Telangana." International Journal of Recent Technology and Engineering (IJRTE) 11, no. 3 (September 30, 2022): 97–100. http://dx.doi.org/10.35940/ijrte.c7259.0911322.
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Space Based technology both optical and microwave SAR Data is used to monitor the Earth at regular intervals which has its application in various fields viz., agriculture, water, urban and so on. Synthetic Aperture Radar (SAR) has its advantage to penetrate through clouds, day-night imaging, all weather conditions and high resolution making it an effective system for crop monitoring, especially during Monsoon Season, as Optical Sensors doesn’t provide cloud free data. Sentinel-1 data has been used in recent studies to map and monitor rice-growing areas. The Sentinel-1 IW GRD data were used to monitor the ricegrowing area over Mahabubnagar District of Telangana State, which was processed in SNAP Software. Few plots were selected by conducting field survey during Kharif 2021. The Radar Vegetation Index (RVI) have been used to monitor the fluctuations in various stages of rice growth. This paper explains how multi temporal SAR observations can be used to monitor rice growing stages, as well as how to interpret σ°VHand σ° VV back scattering co-efficient.
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Alarcon-Aguirre, Gabriel, Reynaldo Fabrizzio Miranda Fidhel, Dalmiro Ramos Enciso, Rembrandt Canahuire-Robles, Liset Rodriguez-Achata, and Jorge Garate-Quispe. "Burn Severity Assessment Using Sentinel-1 SAR in the Southeast Peruvian Amazon, a Case Study of Madre de Dios." Fire 5, no. 4 (July 8, 2022): 94. http://dx.doi.org/10.3390/fire5040094.
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Fire is one of the significant drivers of vegetation loss and threat to Amazonian landscapes. It is estimated that fires cause about 30% of deforested areas, so the severity level is an important factor in determining the rate of vegetation recovery. Therefore, the application of remote sensing to detect fires and their severity is fundamental. Radar imagery has an advantage over optical imagery because radar can penetrate clouds, smoke, and rain and can see at night. This research presents algorithms for mapping the severity level of burns based on change detection from Sentinel-1 backscatter data in the southeastern Peruvian Amazon. Absolute, relative, and Radar Forest Degradation Index (RDFI) predictors were used through singular polarization length (dB) patterns (Vertical, Vertical-VV and Horizontal, Horizontal-HH) of vegetation and burned areas. The Composite Burn Index (CBI) determined the algorithms’ accuracy. The burn severity ratios used were estimated to be approximately 40% at the high level, 43% at the moderate level, and 17% at the low level. The validation dataset covers 384 locations representing the main areas affected by fires, showing the absolute and relative predictors of cross-polarization (k = 0.734) and RDFI (k = 0.799) as the most concordant in determining burn severity. Overall, the research determines that Sentinel-1 cross-polarized (VH) data has adequate accuracy for detecting and quantifying burns.
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Du, Kai, Huaguo Huang, Yuyi Zhu, Ziyi Feng, Teemu Hakala, Yuwei Chen, and Juha Hyyppä. "Simulation of Ku-Band Profile Radar Waveform by Extending Radiosity Applicable to Porous Individual Objects (RAPID2) Model." Remote Sensing 12, no. 4 (February 19, 2020): 684. http://dx.doi.org/10.3390/rs12040684.
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Similar to light detection and ranging (lidar), profile radar can detect forest vertical structure directly. Recently, the first Ku-band profile radar system designed for forest applications, called Tomoradar, has been developed and evaluated in boreal forest. However, the physical relationships between the waveform and forest structure parameters such as height, leaf area index (LAI), and aboveground biomass are still unclear, which limits later forestry applications. Therefore, it is necessary to develop a theoretical model to simulate the relationship and interpret the mechanism behind. In this study, we extend the Radiosity Applicable to Porous IndiviDual objects (RAPID2) model to simulate the profile radar waveform of forest stands. The basic assumption is that the scattering functions of major components within forest canopy are similar between profile radar and the side-looking radar implemented in RAPID2, except several modifications. These modifications of RAPID2 mainly include: (a) changing the observation angle from side-looking to nadir-looking; (b) enhancing the ground specular scattering in normal direction using Fresnel coefficient; (c) increasing the timing resolution and recording waveform. The simulated waveforms were evaluated using two plots of Tomoradar waveforms at co- and cross- polarizations, which are collected in thin and dense forest stands respectively. There is a good agreement (R2 ≥ 0.80) between the model results and experimental waveforms in HH and HV polarization modes and two forest scenes. After validation, the extended RAPID2 model was used to explore the sensitivity of the stem density, single tree LAI, crown shape, and twig density on the penetration depth in the Ku-band. Results indicate that the backscattering of the profile radar penetrates deeper than previous studies of synthetic aperture radar (SAR), and the penetration depth tends to be several meters in Ku-band. With the increasing of the needle and twig density in the microwave propagation path, the penetration depth decreases gradually. It is worth noting that variation of stem density seems to have the least effect on the penetration depth, when there is no overlapping between the single tree crowns.
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Solano-Perez, Jose Antonio, María-Teresa Martínez-Inglés, Jose-Maria Molina-Garcia-Pardo, Jordi Romeu, Lluis Jofre, José-Víctor Rodríguez, and Antonio Mateo-Aroca. "Linear and Circular UWB Millimeter-Wave and Terahertz Monostatic Near-Field Synthetic Aperture Imaging." Sensors 20, no. 6 (March 11, 2020): 1544. http://dx.doi.org/10.3390/s20061544.
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Millimeter-wave and terahertz frequencies offer unique characteristics to simultaneously obtain good spatial resolution and penetrability. In this paper, a robust near-field monostatic focusing technique is presented and successfully applied for the internal imaging of different penetrable geometries. These geometries and environments are related to the growing need to furnish new vehicles with radar-sensing devices that can visualize their surroundings in a clear and robust way. Sub-millimeter-wave radar sensing offers enhanced capabilities in providing information with a high level of accuracy and quality, even under adverse weather conditions. The aim of this paper was to research the capability of this radar system for imaging purposes from an analytical and experimental point of view. Two sets of measurements, using reference targets, were performed in the W band at 100 GHz (75 to 110 GHz) and terahertz band at 300 GHz (220 to 330 GHz). The results show spatial resolutions of millimeters in both the range (longitudinal) and the cross-range (transversal) dimensions for the two different imaging geometries in terms of the location of the transmitter and receiver (frontal or lateral views). The imaging quality in terms of spatial accuracy and target material parameter was investigated and optimized.
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Kurdyanto, Rachmat Agus, Nurhayati Nurhayati, Puput Wanarti Rusimamto, and Farid Baskoro. "STUDY COMPARATIVE OF ANTENNA FOR MICROWAVE IMAGING APPLICATIONS." INAJEEE Indonesian Journal of Electrical and Eletronics Engineering 3, no. 2 (August 28, 2020): 41. http://dx.doi.org/10.26740/inajeee.v3n2.p41-47.
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AbstractMicrowave can be applied for telecommunicaions, radar and microwave imaging. This wave has been widely used in everyday life, such as in the industrial word in the fields of robotics, microwave vision, imaging burrier objects, vehicular guidance, biomedical imaging, remote sensing, wheater radar, target tracking, and other apllications. Microwave imaging is a technology that uses electromagnetic waves at frequencies from Megahertz to Gigahertz. Utilization of microwave imaging in addition to information technology and telecommunications, this wave application can be used to process an image because of its ability to penetrate dielectric materials. The purpose of writing this article is to determine microwave imaging application, the working principle of antennas used for microwave imaging applications and antenna specifications used for microwave imaging applications. Microwave imaging research has been carried out using several different type of antennas such as vivaldi and monopole antennas. Where the signal tha is transmitted and will be exposed to the object will send a different return signal so that an image of an object will be obtained which will be processed on the computer. The working frequency of the antenna for microwave imaging applications is in a wide frequency range (UWB antenna). The antennas that are applied include the vivaldi antenna which works at a frequency of 1-11 GHz and a monopole antenna that works at a frequency 1,25-2,4 GHz for biomedical imaging applications, while for radar applications in the construction field it can use a frequency of 0,5-40 GHz.