The aim of this work was to investigate if interesting patterns could be found in time series radar data that had been discretized by the algorithm ARAVQ into symbolic representations and if the ARAVQ thus might be suitable for use in the radar domain. An experimental study was performed where the ARAVQ was used to create symbolic representations of data sets with radar data. Two experiments were carried out that used a Markov model to calculate probabilities used for discovering potentially interesting patterns. Some of the most interesting patterns were then investigated further. Results have shown that the ARAVQ was able to create accurate representations for several time series and that it was possible to discover patterns that were interesting and represented higher level concepts. However, the results also showed that the ARAVQ was not able to create accurate representations for some of the time series.

In diesem Beitrag wird aufgezeigt, wie die Firma ILV durch langjährige Beteiligung an Forschungs- und Entwicklungsvorhaben sowie durch Industrieerprobung von innovativen Technologien erfolgreich im In- und Ausland arbeitet. Vorgestellt werden schwerpunkthaft Ergebnisse der Anwendung von Satellitenbilddaten im visuellen Bereich und von Radardaten sowie Erfahrungen bei der Einführung der digitalen Luftbildkameratechnik. Berichte aus der Praxis des digitalen Bildfluges im Ausland auch aus Sicht des Auftraggebers für geologische und geotechnische Fragestellungen und der Industrieerprobung von Multibeam-Sonar-Technik zeigen die innovativen Potentiale dieser Technologien. / In this paper, it is shown how the company ILV works successfully domestically and abroad by long standing involvement in research and development projects as well as by industrial testing of innovative technologies. The focus of the paper are results of application of satellite images in visual range and of radar data as experiences with the introduction of digital airborne camera technique. Field notes about digital photo flight abroad – also from the view of the customer for geological and geotechnical problems – and about industrial testing of Multi-beam Sonar Technique show the innovative potentials of these technologies.

Instead of being out at airports for the sake of testing radar data in Visual Docking Guiding System, one could use emulated radar data to function as real radar data. In this thesis, real radar data processed into binary files are, observed and dissembled to use reverse engineering and in such a way emulate similar binary files. The same software used on real radar data binary files is used to process the emulated ones to detect an object at a certain distance. Using reverse engineering could not on its own result in an emulated radar data binary file. Finally trial and error resulted in a file which gave object detection at a distance of above 21 meters as targeted in this thesis. Furthermore, as future work might be found by targeting other and further distances.

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Weather radars are increasingly used for the study of clouds, understanding the precipitation systems and also for forecasting very short range weather (one hour to a few hours). Now, Doppler Weather Radar (DWR) data are available in India and it is possible to study cloud properties at fine temporal and spatial scales. Radar is a complex system and calibration of a radar is not an easy job. But derived cloud properties strongly depend on the absolute magnitude of the reflectivity. Therefore, there is a need to check how data from two or more radars compare if they measure a common volume. Chennai and SHAR radars are within 66 km from each other, and the data collected during their calibration and intercomparison experiment in 2006 enables the comparison of their reflectivity(Z) values. Individual reflectivity are compared after plotting SHAR versus Chennai in a scatter plot. Fitting a least square linear best fit line shows that the intercept has a value around 6 dBZ and the slope of the line is 1.06. Thus, there is a trend as well, and the difference between the two radars increase with Z, and for Z around 40 dBZ (for SHAR DWR), the difference between the two is around 8.5 dBZ. Visual intercomparison also validated the results. Data from the two radars are compared with Precipitation Radar (PR) data on board TRMM satellite. TRMM radar slightly overestimates compared to Chennai radar above the range of 30 dBZ. After standardized, SHAR data is used for understanding the evolution and propagation of cloud systems. The diurnal variation in convection is strong in the study region, with increase around local evening and morning and weakening around midnight except in December. Average liquid water content in the clouds is about 0.5 gm/m3. There is some seasonal dependence but no clear dependence on cloud size. Smaller systems of May have more liquid water content compared to larger ones. For nowcasting vertically projected maximum reflectivity is taken. A threshold of 30 dBZ is set to identify the cloud systems. Both center of gravity tracking (CG) and cross-correlation (CC) methods are used to track them. Frequent merging and splitting is common in the clouds which makes storm tracking difficult. Tracking by CC is giving better result than that by the CG method in the case of large systems (i.e., clusters). For smaller systems (individual cloud systems), CC method gives better result than CG method but not as good as cluster.

In diesem Beitrag wird aufgezeigt, wie die Firma ILV durch langjährige Beteiligung an Forschungs- und Entwicklungsvorhaben sowie durch Industrieerprobung von innovativen Technologien erfolgreich im In- und Ausland arbeitet. Vorgestellt werden schwerpunkthaft Ergebnisse der Anwendung von Satellitenbilddaten im visuellen Bereich und von Radardaten sowie Erfahrungen bei der Einführung der digitalen Luftbildkameratechnik. Berichte aus der Praxis des digitalen Bildfluges im Ausland auch aus Sicht des Auftraggebers für geologische und geotechnische Fragestellungen und der Industrieerprobung von Multibeam-Sonar-Technik zeigen die innovativen Potentiale dieser Technologien. / In this paper, it is shown how the company ILV works successfully domestically and abroad by long standing involvement in research and development projects as well as by industrial testing of innovative technologies. The focus of the paper are results of application of satellite images in visual range and of radar data as experiences with the introduction of digital airborne camera technique. Field notes about digital photo flight abroad – also from the view of the customer for geological and geotechnical problems – and about industrial testing of Multi-beam Sonar Technique show the innovative potentials of these technologies.

L’étude de la diffusion des ondes électromagnétiques par une surface rugueuse aléatoire est de première importance dans de nombreuses disciplines et conduit à diverses applications notamment pour le traitement des surfaces par télédétection. En connaissant les modes de rétrodiffusion, on peut détecter la présence de la rugosité aléatoire indésirable de la surface de réflection telle que le réflecteur d'antenne et par conséquent trouver un moyen de corriger ou compenser les erreurs de phase. Cette thèse porte sur l’obtention de l'humidité du sol de surface à partir de mesures radar. La description de la surface rugueuse de façon aléatoire est présentée, suivie par les interactions d'ondes électromagnétiques avec les média. En particulier, un modèle d'équation intégrale avancé (AIEM) est introduit. La validité du modèle AIEM, qui est adopté comme modèle de travail, se fait par une large comparaison avec des simulations numériques et des données expérimentales. On analyse également les caractéristiques des configurations radar bistatique et on étudie la sensibilité de la diffusion bistatique à l'humidité du sol et à la rugosité de surface et, dans le même temps, le cadre de la détermination de l'humidité du sol à partir de mesures radar utilisant un réseau de neurones à base de filtres de Kalman récurrents est présenté. La formation du réseau et l'inversion des données sont décrits. / Electromagnetic waves scattering from a randomly rough surface is of palpable importance in many fields of disciplines and bears itself in various applications spanned from surface treatment to remote sensing of terrain and sea. By knowing the backscattering patterns, one may detect the presence of the undesired random roughness of the reflection surface such as antenna reflector and accordingly devise a means to correct or compensate the phase errors. Therefore, it has been both theoretically and practically necessary to study the electromagnetic wave scattering from the random surfaces. This dissertation focuses on the retrieval of surface soil moisture from radar measurements. The description of the randomly rough surface is presented, followed by the electromagnetic wave interactions with the media. In particular, an advanced integral equation model (AIEM) is introduced. The validity of the AIEM model, which is adopted as a working model, is made by extensive comparison with numerical simulations and experimental data. Also analyzes the characteristics of the bistatic radar configurations and dissects the sensitivity of bistatic scattering to soil moisture and surface roughness of soil surfaces. Meanwhile presents a framework of soil moisture retrieval from radar measurements using a recurrent Kalman filter-based neural network. The network training and data inversion are described in detail.

Rainfall affects the performance of traffic operations and endangers safety. A common and conventional method (rain gauges) for rainfall measurements mostly provide precipitation records in hourly and 15-minute intervals. However, reliability, continuity, and wide area coverage pose challenges with this data collection method. There is also a greater likelihood for data misrepresentation in areas where short duration rainfall is predominant, i.e., reported values may not reflect the actual equivalent rainfall intensity during subintervals over the entire reporting period. With recent weather and climate patterns increasing in severity, there is a need for a more effective and reliable way of measuring rainfall data used for traffic analyses. This study deployed the use of precipitation radar data to investigate the spatiotemporal effect of rainfall on freeways in Jacksonville, Florida. The linear regression analysis suggests a speed reduction of 0.75%, 1.54%, and 2.25% for light, moderate, and heavy rainfall, respectively. Additionally, headways were observed to increase by 0.26%, 0.54%, and 0.79% for light, moderate, and heavy rainfall, respectively. Measuring precipitation from radar data in lieu of using rain gauges has potential for improving the quality of weather data used for transportation engineering purposes. This approach addresses limitations experienced with conventional rain data, especially since conventional collection methods generally do not reflect the spatiotemporal distribution of rainfall.

Analytics tool for radar data was a project that started when radar specialists at Saab needed to modernize their tools that analyzes binary encoded radar data. Today, the analysis is accomplished using inadequate and ineffective applications not designed for that purpose, and consequently this makes the analysis tedious and more difficult compared to using an appropriate interface. The applications had limitations regarding different radar systems too, which restricted their usage significantly. The solution was to design a new software that imports, translates and visualizes the data independent of the radar system. The software was developed with several parts that communicates with each other to translate a binary file. A binary file consists of a series of bytes containing the information of the targets and markers separating the revolutions of the radar. The byte stream is split according to the ASTERIX protocol that defines the length of each Data Item and the extracted positional values are stored in arrays. The code is then designed to convert the positional values to cartesian coordinates and plot them on the screen. The software has implemented features such as play, pause, reverse and a plotting history that allows the user to analyze the data in a simple and user-friendly manner. There are also numerous ways the software could be extended. The code is constructed in such a way that new features can be implemented for additional analytical abilities without affecting the components already designed.

Honeywell Technology Solutions Lab, India / Weather is a major contributing factor in aviation accidents, incidents and delays. Doppler weather radar has emerged as a potent tool to observe weather. Aircraft carry onboard radars but their range and angular resolution are limited. Networks of ground-based weather radars provide extensive coverage of weather over large geographic regions. It would be helpful if these data can be transmitted to the pilot. However, these data are highly voluminous and the bandwidth of the ground-air communication links is limited and expensive. Hence, these data have to be compressed to an extent where they are suitable for transmission over low-bandwidth links. Several methods have been developed to compress pictorial data. General-purpose schemes do not take into account the nature of data and hence do not yield high compression ratios. A scheme for extreme compression of weather radar data is developed in this thesis that does not significantly degrade the meteorological information contained in these data. The method is based on contour encoding. It approximates a contour by a set of systematically chosen ‘control points’ that preserve its fine structure up to a certain level. The contours may be obtained using a thresholding process based on NWS or custom reflectivity levels. This process may result in region and hole contours, enclosing `high' or `low' areas, which may be nested. A tag bit is used to label region and hole contours. The control point extraction method first obtains a smoothed reference contour by averaging the original contour. Then the points on the original contour with maximum deviation from the smoothed contour between the crossings of these contours are identified and are designated as control points. Additional control points are added midway between the control point and the crossing points on either side of it, if the length of the segment between the crossing points exceeds a certain length. The control points, referenced with respect to the top-left corner of each contour for compact quantification, are transmitted to the receiving end. The contour is retrieved from the control points at the receiving end using spline interpolation. The region and hole contours are identified using the tag bit. The pixels between the region and hole contours at a given threshold level are filled using the color corresponding to it. This method is repeated till all the contours for a given threshold level are exhausted, and the process is carried out for all other thresholds, thereby resulting in a composite picture of the reconstructed field. Extensive studies have been conducted by using metrics such as compression ratio, fidelity of reconstruction and visual perception. In particular the effect of the smoothing factor, the choice of the degree of spline interpolation and the choice of thresholds are studied. It has been shown that a smoothing percentage of about 10% is optimal for most data. A degree 2 of spline interpolation is found to be best suited for smooth contour reconstruction. Augmenting NWS thresholds has resulted in improved visual perception, but at the expense of a decrease in the compression ratio. Two enhancements to the basic method that include adjustments to the control points to achieve better reconstruction and bit manipulations on the control points to obtain higher compression are proposed. The spline interpolation inherently tends to move the reconstructed contour away from the control points. This has been somewhat compensated by stretching the control points away from the smoothed reference contour. The amount and direction of stretch are optimized with respect to actual data fields to yield better reconstruction. In the bit manipulation study, the effects of discarding the least significant bits of the control point addresses are analyzed in detail. Simple bit truncation introduces a bias in the contour description and reconstruction, which is removed to a great extent by employing a bias compensation mechanism. The results obtained are compared with other methods devised for encoding weather radar contours.