SCIENTIFIC AND TECHNICAL AEROSPACE REPORTS
A Biweekly Publication of the National Aeronautics and Space Administration
VOLUME 44, ISSUE 5 - March 10, 2006
32 COMMUNICATIONS AND RADAR
Includes radar; radio, wire, and optical communications; land and global communications; communications theory.
For related information see also 04 Aircraft Communications and Navigation; and 17 Space Communications, Spacecraft Communications, Command and Tracking; for search and rescue, see 03 Air Transportation and Safety; and 16 Space Transportation and Safety.
20060006704 National Telecommunications and Information Administration, Boulder, CO USA
Phased Array Antenna Pattern Variation with Frequency and Implications for Radar Spectrum Measurements
Sanders, F. H.; Ramsey, B. J.; Dec. 2005; 36 pp.; In English Report No.(s): PB2006-105507; NTIA-TR-06-436; No Copyright; Avail.: National Technical Information Service (NTIS)
Measured antenna patterns of an end-fed slotted waveguide antenna and a phased-array patch antenna used in maritime radionavigation radars across the frequency range 8500-10800 MHz are presented along with a measurement technique that characterizes the antenna patterns as a function of frequency. The frequency-dependent variation in the measured pattern of the slotted waveguide is compared to the frequency dependence of an ideal pattern based on the slot geometry. The implications for radar emissions measurement techniques are discussed. NTIS
Antenna Arrays; Antenna Radiation Patterns; Frequency Distribution; Phased Arrays; Radar Antennas; Radar Measurement
20060006808 Research and Technology Organization, Neuilly-sur-Seine, France
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Target Identification and Recognition using RF Systems
October 2004; 450 pp.; In English; RTO Sensors and Electronics Technology Panel (SET) Symposium, 11-13 Oct. 2004, Oslo, Norway; See also 20060006809 - 20060006843 Report No.(s): RTO-MP-SET-080; AC/323(SET-080)TP/50; Copyright; Avail.: CASI: C01, CD-ROM: A19, Hardcopy
The goal of this symposium was to describe the current and projected capability of RF systems for Non- Cooperative Target Identification/Recognition (NCTI/NCTR) at long range and in all weather conditions. Specific objectives were to review NCTI/NCTR R&D efforts available to NATO nations, suggest how and when this technology may contribute to an operational Combat Identification (CID) capability, and address coalition interoperability issues. The symposium was organized along the following themes: NCTI/NCTR of air targets, surface targets, passive RF systems & technology, and countermeasures against NCTI/NCTR.
The first half of this three-day symposium was classified NATO (S) and consisted of twenty-three oral presentations; these papers are available in a classified supplement to Symposium Proceedings. The second-half consisted of eighteen unclassified oral presentations and sixteen unclassified posters that were open to Partnership-for-Peace (PfP) nations. The symposium started with overview presentations of three active SET TGs: SET-053 Ground Target Recognition by Radar , SET-068 Modeling, Analysis and Recognition of Radar Signatures for Non- Cooperative Aircraft Identification , and SET-069 Advanced mmW Techniques for Ground Target Acquisition . Chairmen of these TGs described their Programmes of Work and presented major results; much of the work discussed was later elaborated by other oral and poster presentations.
Most of the contributed papers discussed the state-of-the-art and problems associated with noncooperative aircraft and ground vehicle recognition. Target classifiers were based mostly on analysis of high range resolution (HRR) profiles and synthetic aperture radar (SAR) or inverse synthetic aperture radar (ISAR) image analysis. A recurrent theme was the comparison of classification results based on real data with results obtained from synthetic (model) data. Numerous presentations described and compared the relative merits of various computational electromagnetic codes for predicting synthetic target signatures and imagery. Various target classification algorithms and/or systems were described and compared.
One general observation is that each classifier described performs about as well as another; there is no compelling reason to chose a particular classifier. This conclusion seems to be independent of target type.Afew fielded systems consisting of sensor and classifier were described. Other topics included the contribution of RF polarimetry to target ID, the application of joint time-frequency analysis for improving radar imagery, and passive bi/multi-static sensor systems for covertly obtaining target data. The capability of NCTI/NCTR using HF radar was described in a contribution from Australia. Derived from text
Synthetic Aperture Radar; Radar Imagery; Image Analysis; High Resolution; Classifications; Frequencies; Targets; Target Acquisition; Target Recognition; Polarimetry
20060006809 QinetiQ Ltd., Malvern, UK
Bayesian Approach to Exploiting prior Targeting Information within a Weapon Seeker
Copsey, Keith; Lane, RIchard O.; Manchanda, Sunil; Webb, Andrew R.; Target Identification and Recognition using RF Systems; October 2004; 13 pp.; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
This paper considers an automatic target recognition (ATR) application in which a targeting sensor is used to guide a seeker-equipped weapon to an area containing high-value relocatable targets. The weapon seeker then needs to engage the high value targets, while minimising collateral damage. A Bayesian approach is proposed that enables the weapon seeker to exploit the targeting information before making its final decision. Specifically, the approach matches the scenes in the seeker domain with those from the targeting sensor, while taking into account uncertainty and data latency. The proposed solution utilizes a Bayesian technique known as particle filtering. This paper outlines the approach, and presents results for a synthetic example. Future work will conduct a performance assessment using scenarios derived from real long-range and short-range SAR imagery. Author
Bayes Theorem; Target Recognition; Synthetic Aperture Radar; Radar Imagery; Optimization
20060006810 Academy of Sciences of the Ukraine, Kharkov, Ukraine
Through Wall Detection and Recognition of Human Beings using Noise Radar Sensors
Lukin, Konstantin; Konovalov, Vladimyr; Target Identification and Recognition using RF Systems; October 2004, pp. P15-1 - P15-11; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Elaboration of a new approach to solving of a contradictory and challenging problem of through wall detection radar design is the main goal of the paper. Two types of radars have been investigated: (1) CW radar that uses pseudo-random sequence (PRS) of the maximal length (m-sequence), hereinafter referred to as PRS-radar and (2) CW radar with use of the noise waveform at corresponding carrier frequency referred to as Noise Radar. Besides, notional design of Software Noise Radar for these applications is briefly considered. Derived from text
Radar Detection; Waveforms; Carrier Frequencies; Continuous Wave Radar; Detection
20060006811 Chan Technologies, Inc., Brampton, Ontario, Canada
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Accurate Radar Cross Section Modelling of Jet Inlets and Engines
Chan, Kwok Kee; Target Identification and Recognition using RF Systems; October 2004, pp. P16-1 - P16-9; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Most of the industrial software codes used for the prediction of the radar cross-section (RCS) of aircrafts are based on ray tracing. While ray based methods give useful scattered fields from the skin of the aircraft illuminated by an incident plane wave, they largely fail to predict the returns from cavities onboard. As a possible enhancement to these ray-tracing programs, an auxiliary program based on the modal method was developed to predict the scattering of electrically large and complex jet inlets and engines. It is assumed here that these structures can be approximated by a series of rectangular, circular, coaxial and sectoral waveguide sections. Field matching technique is used to give the generalized scattering matrices of the junctions between these waveguide sections. By combining the scattering matrices of the waveguide sections representing the inlet and engine, an overall S-matrix is obtained. Knowing the modes induced at the inlet aperture by the incident wave, the scattered fields from the inlet and engine can be readily predicted in all directions. Such software has been developed. Monostatic RCS measurements of a 0.706m diameter test cylinder containing 30 skewed blades mounted on a centre shaft with a conical hub have been performed at X-band. The dimensions of the structure, the number and orientation of the blades are consistent with existing jet engines. Good agreement between predictions and measurements verify the developed software and analytical method used. This software could generate the database of RCS returns for a given engine over a wide range of aspect angles. Author
Jet Engines; Radar Cross Sections; Engine Inlets; Mathematical Models
20060006812 National Technical Univ., Athens, Greece
Comparison of Several Spectral Estimation Methods for Application to ISAR Imaging
Karakasiliotis, A.; Frangos, P.; Target Identification and Recognition using RF Systems; October 2004, pp. 11-1 - 11-13; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
During the last decade, several spectral estimation techniques have been proposed for application to SAR/ISAR imaging. The present study attempts to shed light to a number of parametric spectral estimation methods, employed for ISAR imaging of aircraft targets. We focus on performance comparison with respect to 1-D and 2-D image resolution. Auto-regressive methods and MUSIC algorithm are examined and simulated, based on synthetic radar data, for both 1-D (range profiles) and 2-D (ISAR images) cases. Author
Radar Data; Imaging Techniques; Synthetic Aperture Radar; Estimating; Image Resolution
20060006813 Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek, The Hague, Netherlands
Optimizing Single Sweep Range and Doppler Processing for FMCW Radar using Inverse Filtering
deJong, A. J.; vanDorp, Ph.; Target Identification and Recognition using RF Systems; October 2004, pp. 34-1 - 34-9; In English; See also 20060006808; Original contains black and white illustrations; Copyright; Avail.: CASI: A02, Hardcopy;
Available from CASI on CD-ROM only as part of the entire parent document We discuss range and Doppler processing for FMCW radar using only a single pulse or frequency sweep. The first step is correlation processing, for which the range and Doppler resolution are limited by the ambiguity function. We show that this resolution can be optimized with an additional inverse filtering step. The method is demonstrated for sinusoidal FMCW radar measurements. Several regularized inverse filters were compared and the non-adaptive pseudo inverse filter gave the best results. Author
Doppler Radar; Radar Measurement; Adaptive Filters; Frequencies
20060006815 Norwegian Defence Research Establishment, Kjeller, Norway
Time-Frequency Signatures of a Moving Target in SAR Images
Sparr, Trygve; Target Identification and Recognition using RF Systems; October 2004, pp. P8-1 - P8-7; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Moving targets within SAR scenes are distorted depending on the particulars of the target motion. For small motions, the uncompensated phase of a point reflector is a sum of a term proportional to the range component of the target motion, and a more complicated term depending on the azimuth motion. The resulting phase may be analysed with time-frequency techniques since the motion effect may alternatively be seen as a time dependent Doppler frequency.An experiment performed with a moving target within a scene collected by the German E-SAR system gave a signature that agrees well with theoretical predictions. Time-frequency analysis, using the smoothed pseudoWigner-Ville method, gave a linear chirp with superimposed oscillations as predicted from the theory and the target motion. Author
Synthetic Aperture Radar; Radar Imagery; Time Dependence; Oscillations; Distortion
20060006816 Defence Science and Technology Organisation, Edinburgh, Australia
Target Classification, Recognition and Identification with HF Radar
Anderson, Stuart J.; Target Identification and Recognition using RF Systems; October 2004, pp. 25-1 - 25-20; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy;
Available from CASI on CD-ROM only as part of the entire parent document Radars operating in the HF band achieve extremely long range detection by exploiting propagation modes which preclude many of the standard target classification techniques, at least in their conventional form. Yet, in order to take full advantage of an over-the-horizon detection capability, reliable target classification, recognition and identification is essential. This paper explores the options for target classification at HF, reviews some of the results which have been achieved, mainly but not exclusively with reference to skywave radars, and assesses the prospects for operational target classification, recognition and identification. Derived from text
Target Recognition; Propagation Modes; Classifications; Sky Waves
20060006817 Thales Airborne Systems, UK
A Doppler-Based Target Classifier Using Linear Discriminants and Principal Components
Stove, A. G.; Target Identification and Recognition using RF Systems; October 2004, pp. 26-1 - 26-12; In English; See also 20060006808; Original contains black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
This paper describes the design of the automatic target classifier which has been introduced into the AMSTAR Battlefield Surveillance Radar. It discusses the requirements which have driven the design of the classifier, the data which is used to make the classification, the choice of Linear Discriminant Analysis as one of the classification techniques used and the use of Principal Components Analysis to simplify the training of the discriminator. It also discusses the addition of other classes by the use of other data about the targets. It includes a discussion of the testing of the classifier and the performance achieved. Derived from text
Doppler Radar; Discriminant Analysis (Statistics); Classifiers; Surveillance Radar; Principal Components Analysis
20060006818 Triad A.S., Norway
Recognition of Targets by Linear and Non-Linear (Delta K)Processing of Multi Frequency Data
Gjessing, D. T.; Saebboe, J.; Helleren, OE.; Target Identification and Recognition using RF Systems; October 2004, pp. 28-1 - 28-12; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Multi frequency data from continuous wave radar is used to recognize air, sea and land targets. Target range profile data is extracted both from the linear combination of the frequencies and the non-linear Delta K processing. The results are discussed in light of the motion pattern and the vibration of the target. Continuous wave data offers long integration time for Doppler processing, which can be used to get high-resolution Doppler signatures of the targets. These features are discussed as target classifiers. The paper describes the technology and presents some experimental results. The application and limitations of the technology is discussed with focus on integration in a pulsed system. Author
High Resolution; Continuous Radiation; Continuous Wave Radar; Signatures; Classifiers; Frequencies
20060006819 FGAN-FOM Research Inst. for Optronics and Pattern Recognition, Ettlingen, Germany
Kernel Machines for Object Classification in High-Resolution SAR Data
Middelmann,W.; Thoennessen, U.; Target Identification and Recognition using RF Systems; October 2004, pp. 30-1 - 30-13; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
The focus of this paper is the classification of military vehicles in high-resolution SAR images in an ATR framework. The usage of kernel machine classifiers is discussed.Anew kernel machine, the relevance vector machine with integrated generator (RVMG) is introduced. Here, a single parameter controls the trade-off between speed and classification quality. Moreover classification heuristics and an adaptive feature extraction are used. These methods enable an improvement of the classification quality as well as a reduction of the computational effort. A parametrized reject criterion is presented to handle the classification of confusion objects. Therefore receiver operator characteristic (ROC) curves have been calculated. Tests have been performed using the MSTAR public target dataset and a fully polarimetric dataset from QinetiQ. An assessment of several polarimetric features has been performed. Author
Synthetic Aperture Radar; Classifications; Classifiers; Kernel Functions; Pattern Recognition; Radar Imagery; High Resolution
20060006820 Office National d'Etudes et de Recherches Aeronautiques, France
Full-Polarimetric Analysis of MERIC Air Targets Data
Titin-Schnaider, C.; Brouard, P.; Target Identification and Recognition using RF Systems; October 2004, pp. 39-1 - 39-10; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
This paper addresses the detailed analysis of full polarimetric radar images, obtained from real data, by using the Polarimetry theory parameters. The experimental ground based radar station MERIC has been designed at ONERA to perform full polarimetric measurements on non-cooperative in flight airplanes. The first promising results of an analysis carried out from a MERIC full-polarimetric ISAR image of a liner are presented. Author
Synthetic Aperture Radar; Polarimetry
20060006821 Defence Research and Development Canada, Ottawa, Ontario, Canada
Experimental Facility for Measuring Aircraft Inlet/Engine Radar Cross Section
Wong, S.; Riseborough, E.; Duff, G.; Chan, K. K.; Target Identification and Recognition using RF Systems; October 2004, pp. P3-1 - P3-9; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
A full-size aircraft engine-duct mock-up experimental apparatus has been built to collect cavity radar cross section (RCS) data on aircraft engine inlets. The engine-duct structure is made up of a cylindrical duct with a single fan stage consisting of 30 generic straight fan blades. Experimental results indicate that the azimuthal RCS patterns from the engine-duct are quite complex. Numerical computations using a commercial RCS prediction code are compared with the measured data. The comparisons between measured and computed data have highlighted some of the problems and difficulties currently encountered in cavity RCS modelling. These results indicate that engine-duct RCS modelling is a very challenging problem. Author
Radar Cross Sections; Research Aircraft; Engine Inlets; Cavities; Ducts; Fan Blades
20060006822 Georgia Inst. for Research, Atlanta, GA, USA
Passive Radar Imaging and Target Recognition using Illuminators of Opportunity
Lanterman, Aaron; Target Identification and Recognition using RF Systems; October 2004, pp. 24-1 - 24-9; In English; See also 20060006808; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Passive radar systems that exploit illuminators of opportunity, such as FM radio and television broadcasts, to detect and track airborne targets have been under development for over a decade. This paper reviews efforts to add radar imaging and target recognition capabilities to such systems. We discuss recent developments along two parallel threads: 1) Target recognition via radar cross section (RCS) profiles: In this approach, databases of the RCS of targets at different incident and observed angles are created using method-of-moments computational electromagnetics codes. The extracted RCS profiles for different targets, scaled to account for antenna patterns and atmospheric propagation, are compared to the collected data. A coordinated flight model is used to estimate the aircraft's orientation along its flight path. The low frequencies used in passive radar naturally give stable features well suited for automatic target recognition. 2) Radar imaging: A traditional inverse synthetic aperture approach to forming images with passive radar data results in severe artifacts due to the sparse and irregular Fourier sampling patterns resulting from realistic data collection scenarios. We review the application of a recent optimization-based, region-enhancing imaging algorithm to passive radar imaging that effectively suppresses these artifacts, and illustrate the difficulties posed by the underlying multidimensional auto-focus problem. Derived from text
Radar Imagery; Target Recognition; Radar Cross Sections; Radar Data; Radar Targets; Illuminators; Imaging Radar; Antenna Radiation Patterns
20060006823 Forschungsinstitut fuer Hochfrequenzphysik und Radartechnik, Wachtberg-Werthoven, Germany
Robust Acquisition of Relocatable Targets
Schimpf, Hartmut; Target Identification and Recognition using RF Systems; October 2004, pp. 29-1 - 29-13; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Three target types, namely T72, ZSU 23-4 and BMP-2 were measured in a tower/turntable configuration in several articulations each. A set of geometric, statistical, structural and polarimetric features is used to study the robustness of classification. Based on the Kolmogoroff-Smirnov distance between histograms a metric is defined that at the same time allows to quantify intra-class robustness and inter-class separability for an individual feature. For sets of several features, a simple classification approach in connection with a reference confusion matrix allows to assess the robustness of classification. It is demonstrated, that averaging the feature reference over all available target articulations improves the classification performance as compared to a reference that is based on one articulation only. Also, it is shown that in most cases, the classification is the better the more precisely the target aspect angle can be estimated independently. -- The paper reports work that is done in the framework of the NATO RTO/SET-069 working group. Author
Target Acquisition; Robustness (Mathematics); Radar Tracking; Estimating
20060006824 Forschungsinstitut fuer Hochfrequenzphysik und Radartechnik, Wachtberg-Werthoven, Germany
ATR of Battlefield Targets by SAR - Classification Results Using the Public MSTAR Dataset Compared with a Dataset by QinetiQ, UK
Schumacher, Rolf; Rosenbach, Kh.; Target Identification and Recognition using RF Systems; October 2004, pp. 31-1 - 31-12; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
The development of ATR algorithms and the comparison of different classification schemes is one of the main goals of the SET-053 group. The group mainly focuses on SAR images of stationary ground targets, in which the targets are detected. These single image chips form a databank for ATR evaluation and identification to which the classification schemes can be applied. Because of the inhomogeneous measured and modelled datasets of the different nations we start our evaluation with the public MSTAR dataset, which is used since many years for ATR evaluation and identification. In most of the publications dealing with the MSTAR dataset [1,2,3] classification rates between 97% and 100% could be reached due to the good quality of the chip images (good adjustment, centered, good signal/noise ratio, nearly exact scaling).But these results should not be overestimated because the image quality can decrease having real applications with targets in battlefield situations. We investigate the performance of simple classification approaches when the quality of the MSTAR dataset was degraded by adding noise, decentering the targets and introducing errors in the crossrange scaling. In addition we used a dataset from real field measurements which was made available to the SET-053 group by QinetiQ,UK. As anticipated, the classification rates dropped considerable in all mentioned cases. Consequently changes in the feature extraction schemes were investigated which were able to improve the classification rates again. Additionally we analyze the influence of clutter and target shadow on the classification rate. In both datasets the classification rate decreases when we separate the target from clutter and shadow. This is a hint, that a strict separation and segmentation of target and clutter is necessary to classify the real target. Therefore the targets should be measured independently and, if possible, at different locations, so that the clutter doesn't correlate between the test and training data. The target shadow can be used for additional information dependent on the depression angle. Derived from text
Synthetic Aperture Radar; Classifications; Pattern Recognition; Radar Imagery; Signal to Noise Ratios; Image Resolution
20060006825 QinetiQ Ltd., London, UK
Use of Non-Ideal Training Data in SAR ATR for Targeting
Lycett, S. J.; Denton, J.; Blacknell, D.; Target Identification and Recognition using RF Systems; October 2004, pp. 32-1 - 32-14; In English; See also 20060006808; Original contains black and white illustrations Contract(s)/Grant(s): A/CTA/N03504; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
This paper investigates a template-matching approach to automatic target recognition (ATR) for SAR for the case in which positive identification of a single known target type is required. ATR schemes are necessarily supported by databases of training imagery and of particular interest in this study was the impact on performance of using a database of simulated imagery to match against real in situ SAR imagery. Assessments have been made using 30 cm resolution, X-band, spotlight imagery to provide the in situ test data and training databases firstly based on different examples from the same in situ data to provide an idealised baseline and secondly using simulated imagery. The impact on performance for both single channel and polarimetric data is reported and discussed. Author
Target Recognition; Synthetic Aperture Radar; Radar Imagery; Targets; Superhigh Frequencies
20060006826 Deutsche Forschungsanstalt fuer Luft- und Raumfahrt, Wessling, Germany
ATR Performance within an Extended X-Band Tower-Turntable Database of Highly Resolved Relocatable Targets
Kempf, Timo; Peichl, Markus; Dill, Stephan; Suess, Helmut; Target Identification and Recognition using RF Systems; October 2004, pp. 33-1 - 33-11; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
By means of data from highly resolved tower-turntable ISAR measurements this paper investigates the ATR robustness of small changes in the articulation of targets (e.g. military vehicles) and changes in the incidence angle. The recognition process is based on a template matching method. The two-dimensional templates are generated by extracting the most robust scatterers from the RCS image. Author
Targets; Synthetic Aperture Radar; Robustness (Mathematics); Data Bases
20060006827 QinetiQ Ltd., Malvern, UK
Generation and Validation of a Simulated Radar Ground-Target Database
Andre, D.; Blacknell, D.; Hare, J.; Target Identification and Recognition using RF Systems; October 2004, pp. 35-1 - 35-12; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
We generate simulated (I)SAR imagery of a number of ground vehicles with the program Spectre [1] and validate these against turntable (I)SAR imagery from trials. Spectre employs a Physical Optics/Geometrical Optics (PO-GO) or shooting-bouncing-ray high frequency physics model. This approach is employed as standard for high-frequency electromagnetic scattering calculations from large complex bodies, so it is thought that the results have wide relevance. The effects of CAD model complexity and simulation convergence are considered.We evaluate the suitability of the simulated data for use in a database for various kinds of ATR methodologies. There are difficulties in achieving real-time simulations for ATR so we discuss the alternative route of pre-forming a scattering amplitude data-dome for forming monostatic imagery in real-time. Author
Geometrical Optics; Physical Optics; Radar Targets; Computerized Simulation; High Frequencies
20060006828 National Technical Univ., Athens, Greece
Time-Frequency Analysis of Radar Signals
Boultadakis, G.; Skrapas, K.; Frangos, P.; Target Identification and Recognition using RF Systems; October 2004, pp. 7-1 - 7-19; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
It has been well understood that a given signal can be represented in an infinite number of different ways. Of course, different signal representations can be used for different applications. Despite the fact that the number of ways describing a given signal are countless, the most popular , important and fundamental variables are: time and frequency. The time domain indicates how a signal s amplitude changes over time and the frequency domain indicates how often these changes take place. The key for the description of a signal was to find a form which would unite the variables above. The tool that matched time and frequency was the 'Fourier Transform'. Since its introduction in the nineteenth century, the Fourier Transform has become one of the most widely used signal-analysis tools across many disciplines of science and engineering. The fundamental idea behind Fourier Transform is the decomposition of a signal as the sum of weighted sinusoidal functions of different frequencies. The projection of the values of these sinusoidal functions (each of which is a function with a unique frequency) form the Fourier Transform of the original signal. Despite their simple interpretation of pure frequencies, the Fourier transform is not always the best tool to analyze 'real life signals'. These are usually of finite, perhaps even relatively short duration, and they have frequency contents that change over time. The most common examples of such signals are biomedical, musical and seismic signals. Especially seismic signals are not like sinusoidal functions, extending from negative infinity to positive infinity in time. For such kind of applications, the sinusoidal functions are not good models. Derived from text
Signal Analysis; Fourier Transformation; Frequencies; Radar
20060006829 Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek, The Hague, Netherlands
The Desirability of a NATO-central Database for Non-Cooperative Target Recognition of Aircraft
Gelsema, S. J.; Target Identification and Recognition using RF Systems; October 2004, pp. 23-1 - 23-10; In English; See also 20060006808; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
For a decade, NATO nations, both on their own and within NATO groups have performed studies in the field of Two-dimensional Inverse Synthetic Aperture Radar (2D-ISAR) and High Resolution Radar (HRR) Range Profiles. During that work high-quality radar imagery data of aircraft has become available through measurement campaigns. It was shown that the acquisition of a sufficiently large and representative reference database is a difficult and laborious process. Other database properties, such as its contents, size, upgradability, retrieval speed, operational use, etc. have not received sufficient attention within these studies. In the future, NATO may be playing a major role in maintaining a NATO central database of radar signatures. This paper provides an initial understanding of the operational implications for performing such a task. It argues that, instead of providing a central database to NATO nations, NATO should stimulate the use of decentralized classifiers and databases and ensure that coalition partners can access them via a data network in operational situations. Author
Target Recognition; Synthetic Aperture Radar; Data Bases; Computer Networks; Radar Imagery; Radar Signatures
20060006830 Military Univ. of Technology, Warsaw, Poland
Ground Target Signal Simulation by Real Signal Data Modification
Czarnecki,Withold; Target Identification and Recognition using RF Systems; October 2004, pp. 36-1 - 36-12; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
Simulation techniques offer very often the only realistic methods of signal processing quality assessment. Standard approach to signal simulation needs prior definition of signal model before construction of signal simulation algorithm. Sufficient number of signal data are necessary for definition of good signal model. Signal data available are not always satisfactory numerous. An approach is proposed to cope with this problem by simulating signal realizations as modifications of real, registered signal. Methods of modification of real signals in time-space domain as well as in frequency domain are proposed. Results of simulation experiments are presented. Derived from text
Data Simulation; Signal Processing; Algorithms; Frequencies
20060006832 QinetiQ Ltd., Malvern, UK
An Adaptive Unified Algorithm for Both Detection and Recognition
Copsey, Keith D.; Webber, Chris J. S.; Target Identification and Recognition using RF Systems; October 2004, pp. 38-1 - 38-13; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
An adaptive neural-network approach to target- and clutter-modelling is introduced. A key novelty of this approach is that both targets and clutter can be modelled within the same neural network, so that detection and recognition can take place simultaneously within an integrated framework. The approach can therefore be applied across the spectrum of ATR discrimination levels, e.g.: detection of unknown targets in clutter; detection of specific designated targets in clutter; recognition of target subclass post-detection. The approach is designed to be generically applicable, to data from a variety of sensors, including HRRPs, SAR intensity imagery, complex SAR imagery, visible and EO imagery, and burst-illumination LIDAR. This generic applicability is attributable to the fact that the algorithm adaptively models training-exemplar data of arbitrary type and dimensionality. Unlike many current approaches to target detection, this approach can exploit a wide range of cues for discriminating targets from clutter objects, including detailed grey-level shape information and, for RF sensors, complex/phase information. Furthermore, the approach is quick to use in operation, and has been designed with hardware implementations in mind. Successful results are presented for a target (designated building) detection and identification problem using real SAR imagery. The approach has been designed to have the future potential to offer other very significant new capabilities, e.g. the potential for reducing false-alarm rate in urban clutter and improving robustness to extended operating conditions. Author
Target Acquisition; Target Recognition; Detection; Algorithms; Robustness (Mathematics); Radio Frequencies; Radar Imagery; Optical Radar
20060006833 Danish Defence Research Establishment, Copenhagen, Denmark
Advances of Techniques for Utilizing Polarimetric Features of Radar Targets
Krogager, Ernst; Target Identification and Recognition using RF Systems; October 2004, pp. 40-1 - 40-8; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
The scattering properties of a radar target can only be fully characterized by measuring a scattering matrix in which the elements represent the combinations of transmit and receive polarization states. The amount of information gathered by a traditional single polarization radar may therefore be even very limited, for example when the single polarization response is near zero while the cross polarized return is at a maximum. By polarimetric processing, different scatterers, i.e., scattering mechanisms, can be completely and coherently separated, even if they are located within the same resolution cell of the radar image. This is particularly important in relation to non-cooperative target identification and recognition. Nevertheless, the practical utilization of polarization for optimizing information content has not gained more widespread interest until very recently. This is mainly due to a lack of proper technology in the past, but also due to negative conclusions drawn from early experiments with polarimetric radar. At the moment, significant efforts are put into the development of techniques for efficiently and conveniently handling polarimetric data. Such techniques differ considerably from techniques known from traditional single polarization target imaging, since one has to deal with a matrix for each resolution cell instead of just a single scalar. In this paper, some of the advances and advantages of polarimetric radar techniques will be reviewed and presented in an application-oriented perspective, emphasizing the potential of utilizing the information contained in the polarization transforming properties of radar targets. Author
Target Recognition; Radar Targets; Polarimetry; Cross Polarization; Imaging Techniques; Radar Imagery
20060006834 Office National d'Etudes et de Recherches Aeronautiques, Paris, France
Robust Polarimetric Scatterers Extraction for SAR ATR
Vignaud, Luc; Target Identification and Recognition using RF Systems; October 2004, pp. 41-1 - 41-10; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
We present a new tool for extracting robust and stable polarimetric scatterers from ground target SAR data with applications to Automatic Target Recognition (ATR). This combination of signal processing algorithms enables us to synthesize the fully polarimetric scatterers information contained in a collection of adjacent SAR images (i.e. looks) and derives the probabilities for individual (or groups of) scatterers to be active and stable over a certain observation angle for the target under test. It is based on an autofocus polarimetric version of the CLEAN-RELAX algorithm, which is followed by a tracking on both the position and polarimetric information of the extracted scatterers over some angular extension (or separate looks). A sub-pixel autofocus and a local relaxation is embedded in the algorithm to achieve a better extraction. Residual translations between focused looks are then estimated through a simple correlation scheme or using the following scatterers tracking. Individual extracted scatterers are tracked from one look to another using a matching criteria based both on the distance and the fully polarimetric magnitudes. We then derive the most probable target signature, which may be used as template for classification purposes. This process may also be very useful when working with target variants, in order to define which part of the target may remain stable and potentially useful for the classification stages. Moreover, this makes a tremendous information compression, which becomes mandatory when working with large data collections. We show an application of the technique on a real dataset that was provided by Qinetiq to Nato SET 053 group for ATR evaluation purposes. Author
Synthetic Aperture Radar; Radar Imagery; Polarimetry; Target Recognition; Scattering; Classifications; Estimating; Probability Theory
20060006835 Physics and Electronics Lab. TNO, The Hague, Netherlands
The Role of Feature Enhanced Processing for Automatic Target Recognition using High Resolution Polarimetric SAR Data
vandenBroek, Albertus; Steeghs, Philippe; Dekker, Rob; Target Identification and Recognition using RF Systems; October 2004, pp. 42-1 - 42-15; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
We have studied the effect of feature enhanced processing on the discrimination of targets in high resolution polarimetric ISAR and SAR images. This is done by comparing feature-based classification results for original images and images which have been pre-processed to enhance target features. The data comprised four military targets: T72, ZSU23/4, T62, and BMP2. Images at a resolution of 10 cm have been extracted from the ISAR data for a complete aspect range of 360 degrees. The SAR images were taken from the MSTAR database with a resolution of 30 cm. These images have been processed in order to enhance the geometrical delineation of the targets or to enhance point scattering. We have composed feature vectors out of individual features, which were extracted from the original and the enhanced images. The feature vectors are divided into three categories: radiometric, geometric and polarimetric. A maximum likelihood classifier was used to obtain discrimination results. Knowledge about the aspect angle allows target discrimination per aspect angle interval, which will improve classification results. We have investigated the effect of feature enhanced processing on pose estimation. Pose estimation was obtained from the Radon transform of the original and enhanced imagery.We found that the features extracted from enhanced images give slightly better results compared to features extracted from the original images. For the high-resolution enhanced ISAR data reasonable discrimination (about 80%) was obtained compared to the enhanced MSTAR data (about 60%), when radiometric and geometric features are used. Using the polarimetric features the discrimination results could be improved to 85%. For aspect angle determination using the Radon transformation and for target discrimination per aspect angle interval no significant improvement was obtained using feature enhanced processing. The aspect angle could be determined up to an accuracy of 10-15 degrees, depending on the target. Discrimination per aspect interval using radiometric and geometric features shows results of 90% for the ISAR and 75% for the MSTAR images. Polarimetric information improves the results up to 97% for the ISAR images. Author
Synthetic Aperture Radar; Polarimetry; Radar Imagery; High Resolution; Image Classification; Target Recognition; Scattering; Radar Tracking
20060006837 AMS - Engineering and Operation, Rome, Italy
Super-Resolution Techniques Applied to MSTAR Data
DErcole, Silvio; Target Identification and Recognition using RF Systems; October 2004, pp. P9-1 - P9-18; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
This paper has been produced in the frame of research group for Automatic Target Recognition (ATR), NATO SET 053 TG 29. One of the biggest challenges for automatic target recognition (ATR) methods is the accurate and efficient extraction of features from synthetic aperture radar (SAR) images. The aim of this work is to evaluate the recognition-oriented properties for 2D modified covariance Super-Resolution technique. Recognition-oriented properties in order to enhance features in the scene that are important for recognition purposes. Performances of the technique are evaluated in this paper by testing robustness of preserving and enhancing features extraction. Results indicate that 2D modified covariance Super-Resolution technique formation method provides images with higher resolution of scatterers, and better separability of different regions as compared to conventional SAR images. Author
Target Recognition; Automatic Control; High Resolution; Spectrum Analysis
20060006838 Naval Research Lab., Washington, DC, USA
3-D Time/Frequency-Range-Doppler Signatures for SAR Imaging of Ground Moving Targets
Chen, V. C.; Lipps, R.; Target Identification and Recognition using RF Systems; October 2004, pp. P4-1 - P4-8; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
In this paper, we introduce the concept of 3-D radar signatures in a slow time-range-Doppler, fast time-range-Doppler and frequency-range-Doppler. Then, we describe how to utilize 3-D time or frequency-range-Doppler signatures to extract information for detecting, relocating and re-focusing moving targets. Finally, we use AN/APY-6 X-band radar data for the demonstration of ground moving target detection. Author
Doppler Radar; Target Acquisition; Superhigh Frequencies; Radar Signatures; Radar Data; Frequency Ranges; Imaging Techniques
20060006839 QinetiQ Ltd., Malvern, UK
Bayesian Approach to Recognizing Relocatable Targets
FROM; Copsey, Ketih; Lane, RIchard O.; Manchanda, Sunil; Webb, Andrew R.; Target Identification and Recognition using RF Systems; October 2004, pp. P6-1 - P6-11; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
This paper presents a framework for target acquisition. The targets of interest are relocatable ground vehicles imaged at time t=t(sub 0) by a long range targeting sensor and then at a later time t=t(sub 1) by a weapon platform. The framework must handle several key issues: changes in scene (vehicle movement between t(sub 0) and t(sub 1); incorporation of domain knowledge (terrain and vehicle type); image registration errors; differences in viewing angle; uncertainty in vehicle type, and location. A modular approach is presented in which the key quantities of interest are probability density functions. There are many technical issues that must be addressed and two in particular are highlighted: the development of generalisation procedures between sensors that enable training data gathered with one sensor to be used to classify data obtained from a different RF sensor (specifically, a procedure to enable ISAR data to be exploited); and the development of techniques that use prior knowledge from a targeting sensor to aid a weapon seeker (the use of targeting information to support acquisition). A Bayesian methodology is adopted and the research is set in the target acquisition context. Author
Bayes Theorem; Pattern Registration; Target Acquisition; Radio Frequencies; Probability Density Functions; Image Processing
20060006840 Norwegian Defence Research Establishment, Kjeller, Norway
DRFM-Modulator for HRR-Jamming
Thingsrud, Oyvind; Target Identification and Recognition using RF Systems; October 2004, pp. P7-1 - P7-11; In English; See also 20060006808; Original contains color and black and white illustrations; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
The Digital RF Memory (DRFM) is a key component in modern radar jamming systems. To introduce false targets in a High-Range-Resolution (HRR) radar and other high-resolution imaging radars, a new generation DRFM-system is being developed with far better range resolution and modulation properties. The DRFM also needs better performance in the D/A-converter than in the systems used today, because of the high fidelity jamming signal. This paper is a part of a Master thesis [6] and describes a new type of DRFM-modulator that uses digital signal processing in the frequency-domain for generation of false targets [1]. The modulator is able to produce a radar scene with a number of complex false targets constructed of many single reflectors with individual modulation and with a credible background. Some of the different strategies for the modulator topology will be introduced and discussed. The modulator is being implemented using parallel digital logic in a number of Field Programmable Gate Arrays (FPGA) on a single printed circuit board (PCB) for use in FFIs experimental radar jammer named EKKO II [4]. Author
Radio Frequencies; Printed Circuits; Circuit Boards; Modulators; Jamming
20060006841 Istituto per le Telecomunicazioni e l'Elettronica G. Vallauri, Livorno, Italy
The Polarimetric Dynamical Estimator HRP Improving Success in the Detection Process
Ricci, Angelo M.; Trinci, R.; Target Identification and Recognition using RF Systems; October 2004, pp. P10-1 - P10-9; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
In several circumstances targets at sea are difficult to detect. This difficulty is intrinsically related to the target's physical attributes and its environment (sea and weather conditions). The possibility of detecting and scaling the ATR levels from detection up to characterization depends on such aforesaid difficulties. In any given situation, are there any physical attributes which might enhance and temporarily stabilize the target radar response and/or the background? The existence of such attributes could be initially detected by adopting a series of suitable RF radar parameters. This poster illustrates the results of a technique based on the use of suitable RF parameters, data acquisition and processing methodologies in order to improve the probability of success in the detection process. An agile full polarimetric multi frequency and PWs radar is used to transmit and receive scattered echoes. I and Q channels are acquired using four fast, wide BW A/D converters possessing high throughput to memory. This allows the acquisition of a complete set of scattered radar responses from portions of sea surfaces that probably contain a target. Radar responses (echoes) catalogued in a scattering data bank are then used to feed a recursive d & c algorithm employing the polarimetric estimator which indicates the likely presence of targets in the area. Author
Detection; Polarimetry; Radio Frequencies; Target Recognition; High Resolution
20060006842 Yasotharan (A.), Ontario, Canada
Optimum Time-Frequency Distribution for Detecting a Discrete-Time Chirp Signal in White Gaussian Noise
Yasotharan, A.; Thayaparan, T.; Target Identification and Recognition using RF Systems; October 2004, pp. P11-1 - P11-12; In English; See also 20060006808; Copyright; Avail.: CASI: A03, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
In the continuous-time domain, Maximum-Likelihood (ML) detection of a chirp signal in white Gaussian noise can be done via the line-integral transform of the classical Wigner distribution. The line-integral transform is known variously as the Hough transform and the Radon transform. For discrete-time signals, the Wigner-type distribution defined by Claasen and Mecklenbrauker has become popular as a signal analysis tool. Moreover, it is commonly believed that ML detection of a discrete-time chirp signal in white Gaussian noise can be done via the line-integral transform of the Wigner-Claasen- Mecklenbrauker distribution. This belief is false and results in loss of performance. We derive a Wigner-type distribution for discrete-time signals whose line-integral transform can be used for ML detection of discrete-time chirp signals in white Gaussian noise.We provide simulated Receiver Operating Curves for theWigner- Claasen-Mecklenbrauker distribution based method and the new ML-equivalent method and demonstrate the sub-optimality of the former. Author
Signal Analysis; Maximum Likelihood Estimates; Frequency Distribution; Chirp Signals; Time Signals; White Noise; Signal Detection; Random Noise
20060006843 QinetiQ Ltd., Malvern, UK
Application of Linear Discriminant Analysis to Doppler Classification
Jahangir, M.; Target Identification and Recognition using RF Systems; October 2004, pp. P14-1 - P14-10; In English; See also 20060006808; Original contains color illustrations; Copyright; Avail.: CASI: A02, Hardcopy; Available from CASI on CD-ROM only as part of the entire parent document
In this work the author demonstrated a robust and efficient method for implementing Doppler classification through the use of Linear Discriminant Analysis (LDA). LDAs were used to reduce dramatically the data dimensionality and thereby eliminate redundancy and improve the efficiency of the classifier. The performance was assessed on a three-class problem of personnel, tracked and wheeled vehicles. Real radar data from a ground based system were used in the design and testing of the classifier. The classifier algorithm was optimized by choosing the best set of features that maximized the performance and the bootstrap method was used to measure the confidence interval. It was shown that only the first few LDA features were relevant. At the very least these were shown to contain information regarding the frequency extent of target Doppler sidebands. The classifier was shown to be robust to changes in target viewing geometry and speed. Overall, good classification was achieved for personnel with some misclassification between tracked and wheeled vehicles. Author
Discriminant Analysis (Statistics); Laser Doppler Velocimeters; Radar Data; Classifications; Classifiers
20060007664 Bureau of the Census, Washington, DC, USA
Economic Census 2002: Manufacturing, Industry Series. Telephone Apparatus Manufacturing
Dec. 2004; 50 pp.; In English Report No.(s): PB2006-103313; EC02-31I-334210(RV); No Copyright; Avail.: CASI: A03, Hardcopy
The economic census is the major source of facts about the structure and functioning of the nation's economy. It provides essential information for government, business, industry, and the general public. Title 13 of the USA Code (Sections 131, 191, and 224) directs the Census Bureau to take the economic census every 5 years, covering years ending in 2 and 7. The economic census furnishes an important part of the framework for such composite measures as the gross domestic product estimates, input/output measures, production and price indexes, and other statistical series that measure short-term changes in economic conditions. The Manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The assembling of component parts of manufactured products is considered manufacturing, except in cases where the activity is appropriately classified in construction. NTIS
Census; Communication Equipment; Economic Analysis; Economics; Industries; Manufacturing; Telephones
20060007667 Bureau of the Census, Washington, DC, USA
Economic Census 2002: Manufacturing, Industry Series. Radio and Television Broadcasting and Wireless Communications Equipment Manufacturing
Dec. 2004; 50 pp.; In English Report No.(s): PB2006-103314; EC02-31I-334220(RV); No Copyright; Avail.: CASI: A03, Hardcopy
The economic census is the major source of facts about the structure and functioning of the nation's economy. It provides essential information for government, business, industry, and the general public. Title 13 of the USA Code (Sections 131, 191, and 224) directs the Census Bureau to take the economic census every 5 years, covering years ending in 2 and 7. The economic census furnishes an important part of the framework for such composite measures as the gross domestic product estimates, input/output measures, production and price indexes, and other statistical series that measure short-term changes in economic conditions. The Manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The assembling of component parts of manufactured products is considered manufacturing, except in cases where the activity is appropriately classified in construction. NTIS
Broadcasting; Census; Economic Analysis; Economics; Industries; Manufacturing; Radio Equipment; Television Equipment; Wireless Communication
20060007668 Bureau of the Census, Washington, DC, USA
Economic Census 2002: Manufacturing, Industry Series. Other Communications Equipment Manufacturing
Dec. 2004; 50 pp.; In English Report No.(s): PB2006-103315; EC02-31I-334290(RV); No Copyright; Avail.: CASI: A03, Hardcopy
The economic census is the major source of facts about the structure and functioning of the nation's economy. It provides essential information for government, business, industry, and the general public. Title 13 of the USA Code (Sections 131, 191, and 224) directs the Census Bureau to take the economic census every 5 years, covering years ending in 2 and 7. The economic census furnishes an important part of the framework for such composite measures as the gross domestic product estimates, input/output measures, production and price indexes, and other statistical series that measure short-term changes in economic conditions. The Manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The assembling of component parts of manufactured products is considered manufacturing, except in cases where the activity is appropriately classified in construction. NTIS
Census; Communication Equipment; Economic Analysis; Economics; Industries; Manufacturing
Source: NASA
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