Automatic Adaptation of Airport Surface Surveillance to Sensor Quality

This paper describes a novel method to enhance current airport surveillance systems used in Advanced Surveillance Monitoring Guidance and Control Systems (A-SMGCS). The proposed method allows for the automatic calibration of measurement models and enhanced detection of nonideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the surveillance processing chain and a rule based expert system aimed to change the data processing methods

Gas sensor based on room temperature optical properties of Surface QDs

Self-organized InGaAs QDs are intensively studied for optoelectronic applications. Several approaches are in study to reach the emission wavelengths needed for these applications. The use of antimony (Sb) in either the capping layer or into the dots is one example. However, these studies are normally focused on buried QD (BQD) where there are still different controversial theories concerning the role of Sb. Ones suggest that Sb incorporates into the dot [1], while others support the hypothesis that the Sb occupies positions surrounding the dot [2] thus helping to keep their shape during the capping growth.

Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.

Room temperature photoluminescence of InGaAs Surface Quantum Dots

Self-assembled InGaAs quantum dots show unique physical properties such as three dimensional confinement, high size homogeneity, high density and low number of dislocations. They have been extensively used in the active regions of laser devices for optical communications applications [1]. Therefore, buried quantum dots (BQDs) embedded in wider band gap materials have been normally studied. The wave confinement in all directions and the stress field around the dot affect both optical and electrical properties [2, 3]. However, surface quantum dots (SQDs) are less affected by stress, although their optical and electrical characteristics have a strong dependence on surface fluctuation. Thus, they can play an important role in sensor applications

Aplicaciones de interés forestal de las imágenes obtenidas con el sensor Multi-angle Imaging SpectroRadiometer (MISR)

Las aplicaciones de la teledetección al seguimiento de lo que ocurre en la superficie terrestre se han ido multiplicando y afinando con el lanzamiento de nuevos sensores por parte de las diferentes agencias espaciales. La necesidad de tener información actualizada cada poco tiempo y espacialmente homogénea, ha provocado el desarrollo de nuevos programas como el Earth Observing System (EOS) de la National Aeronautics and Space Administration (NASA). Uno de los sensores que incorpora el buque insignia de ese programa, el satélite TERRA, es el Multi-angle Imaging SpectroRadiometer (MISR), diseñado para capturar información multiangular de la superficie terrestre. Ya desde los años 1970, se conocía que la reflectancia de las diversas ocupaciones y usos del suelo variaba en función del ángulo de observación y de iluminación, es decir, que eran anisotrópicas. Tal variación estaba además relacionada con la estructura tridimensional de tales ocupaciones, por lo que se podía aprovechar tal relación para obtener información de esa estructura, más allá de la que pudiera proporcionar la información meramente espectral. El sensor MISR incorpora 9 cámaras a diferentes ángulos para capturar 9 imágenes casi simultáneas del mismo punto, lo que permite estimar con relativa fiabilidad la respuesta anisotrópica de la superficie terrestre. Varios trabajos han demostrado que se pueden estimar variables relacionadas con la estructura de la vegetación con la información que proporciona MISR. En esta Tesis se ha realizado una primera aplicación a la Península Ibérica, para comprobar su utilidad a la hora de estimar variables de interés forestal. En un primer paso se ha analizado la variabilidad temporal que se produce en los datos, debido a los cambios en la geometría de captación, es decir, debido a la posición relativa de sensores y fuente de iluminación, que en este caso es el Sol. Se ha comprobado cómo la anisotropía es mayor desde finales de otoño hasta principios de primavera debido a que la posición del Sol es más cercana al plano de los sensores. También se ha comprobado que los valores máximo y mínimo se van desplazando temporalmente entre el centro y el extremo angular. En la caracterización multiangular de ocupaciones del suelo de CORINE Land Cover que se ha realizado, se puede observar cómo la forma predominante en las imágenes con el Sol más alto es convexa con un máximo en la cámara más cercana a la fuente de iluminación. Sin embargo, cuando el Sol se encuentra mucho más bajo, ese máximo es muy externo. Por otra parte, los datos obtenidos en verano son mucho más variables para cada ocupación que los de noviembre, posiblemente debido al aumento proporcional de las zonas en sombra. Para comprobar si la información multiangular tiene algún efecto en la obtención de imágenes clasificadas según ocupación y usos del suelo, se han realizado una serie de clasificaciones variando la información utilizada, desde sólo multiespectral, a multiangular y multiespectral. Los resultados muestran que, mientras para las clasificaciones más genéricas la información multiangular proporciona los peores resultados, a medida que se amplían el número de clases a obtener tal información mejora a lo obtenido únicamente con información multiespectral. Por otra parte, se ha realizado una estimación de variables cuantitativas como la fracción de cabida cubierta (Fcc) y la altura de la vegetación a partir de información proporcionada por MISR a diferentes resoluciones. En el valle de Alcudia (Ciudad Real) se ha estimado la fracción de cabida cubierta del arbolado para un píxel de 275 m utilizando redes neuronales. Los resultados muestran que utilizar información multiespectral y multiangular puede mejorar casi un 20% las estimaciones realizadas sólo con datos multiespectrales. Además, las relaciones obtenidas llegan al 0,7 de R con errores inferiores a un 10% en Fcc, siendo éstos mucho mejores que los obtenidos con el producto elaborado a partir de datos multiespectrales del sensor Moderate Resolution Imaging Spectroradiometer (MODIS), también a bordo de Terra, para la misma variable. Por último, se ha estimado la fracción de cabida cubierta y la altura efectiva de la vegetación para 700.000 ha de la provincia de Murcia, con una resolución de 1.100 m. Los resultados muestran la relación existente entre los datos espectrales y los multiangulares, obteniéndose coeficientes de Spearman del orden de 0,8 en el caso de la fracción de cabida cubierta de la vegetación, y de 0,4 en el caso de la altura efectiva. Las estimaciones de ambas variables con redes neuronales y diversas combinaciones de datos, arrojan resultados con R superiores a 0,85 para el caso del grado de cubierta vegetal, y 0,6 para la altura efectiva. Los parámetros multiangulares proporcionados en los productos elaborados con MISR a 1.100 m, no obtienen buenos resultados por sí mismos pero producen cierta mejora al incorporarlos a la información espectral. Los errores cuadráticos medios obtenidos son inferiores a 0,016 para la Fcc de la vegetación en tanto por uno, y 0,7 m para la altura efectiva de la misma. Regresiones geográficamente ponderadas muestran además que localmente se pueden obtener mejores resultados aún mejores, especialmente cuando hay una mayor variabilidad espacial de las variables estimadas. En resumen, la utilización de los datos proporcionados por MISR ofrece una prometedora vía de mejora de resultados en la media-baja resolución, tanto para la clasificación de imágenes como para la obtención de variables cuantitativas de la estructura de la vegetación. ABSTRACT Applications of remote sensing for monitoring what is happening on the land surface have been multiplied and refined with the launch of new sensors by different Space Agencies. The need of having up to date and spatially homogeneous data, has led to the development of new programs such as the Earth Observing System (EOS) of the National Aeronautics and Space Administration (NASA). One of the sensors incorporating the flagship of that program, the TERRA satellite, is Multi-angle Imaging Spectroradiometer (MISR), designed to capture the multi-angle information of the Earth's surface. Since the 1970s, it was known that the reflectance of various land covers and land uses varied depending on the viewing and ilumination angles, so they are anisotropic. Such variation was also related to the three dimensional structure of such covers, so that one could take advantage of such a relationship to obtain information from that structure, beyond which spectral information could provide. The MISR sensor incorporates 9 cameras at different angles to capture 9 almost simultaneous images of the same point, allowing relatively reliable estimates of the anisotropic response of the Earth's surface. Several studies have shown that we can estimate variables related to the vegetation structure with the information provided by this sensor, so this thesis has made an initial application to the Iberian Peninsula, to check their usefulness in estimating forest variables of interest. In a first step we analyzed the temporal variability that occurs in the data, due to the changes in the acquisition geometry, i.e. the relative position of sensor and light source, which in this case is the Sun. It has been found that the anisotropy is greater from late fall through early spring due to the Sun's position closer to the plane of the sensors. It was also found that the maximum and minimum values are displaced temporarily between the center and the ends. In characterizing CORINE Land Covers that has been done, one could see how the predominant form in the images with the highest sun is convex with a maximum in the camera closer to the light source. However, when the sun is much lower, the maximum is external. Moreover, the data obtained for each land cover are much more variable in summer that in November, possibly due to the proportional increase in shadow areas. To check whether the information has any effect on multi-angle imaging classification of land cover and land use, a series of classifications have been produced changing the data used, from only multispectrally, to multi-angle and multispectral. The results show that while for the most generic classifications multi-angle information is the worst, as there are extended the number of classes to obtain such information it improves the results. On the other hand, an estimate was made of quantitative variables such as canopy cover and vegetation height using information provided by MISR at different resolutions. In the valley of Alcudia (Ciudad Real), we estimated the canopy cover of trees for a pixel of 275 m by using neural networks. The results showed that using multispectral and multiangle information can improve by almost 20% the estimates that only used multispectral data. Furthermore, the relationships obtained reached an R coefficient of 0.7 with errors below 10% in canopy cover, which is much better result than the one obtained using data from the Moderate Resolution Imaging Spectroradiometer (MODIS), also onboard Terra, for the same variable. Finally we estimated the canopy cover and the effective height of the vegetation for 700,000 hectares in the province of Murcia, with a spatial resolution of 1,100 m. The results show a relationship between the spectral and the multi-angle data, and provide estimates of the canopy cover with a Spearman’s coefficient of 0.8 in the case of the vegetation canopy cover, and 0.4 in the case of the effective height. The estimates of both variables using neural networks and various combinations of data, yield results with an R coefficient greater than 0.85 for the case of the canopy cover, and 0.6 for the effective height. Multi-angle parameters provided in the products made from MISR at 1,100 m pixel size, did not produce good results from themselves but improved the results when included to the spectral information. The mean square errors were less than 0.016 for the canopy cover, and 0.7 m for the effective height. Geographically weighted regressions also showed that locally we can have even better results, especially when there is high spatial variability of estimated variables. In summary, the use of the data provided by MISR offers a promising way of improving remote sensing performance in the low-medium spatial resolution, both for image classification and for the estimation of quantitative variables of the vegetation structure.

Temperature Sensor Placement Including Routing Overhead and Sampling Inaccuracies

Dynamic thermal management techniques require a collection of on-chip thermal sensors that imply a significant area and power overhead. Finding the optimum number of temperature monitors and their location on the chip surface to optimize accuracy is an NP-hard problem. In this work we improve the modeling of the problem by including area, power and networking constraints along with the consideration of three inaccuracy terms: spatial errors, sampling rate errors and monitor-inherent errors. The problem is solved by the simulated annealing algorithm. We apply the algorithm to a test case employing three different types of monitors to highlight the importance of the different metrics. Finally we present a case study of the Alpha 21364 processor under two different constraint scenarios.

Packaging and testing of fiber Bragg gratings for use as strain sensor for rock specimens

This paper reports a packaging and calibration procedure for surface mounting of fiber Bragg grating (FBG) sensors to measure strain in rocks. The packaging of FBG sensors is performed with glass fiber and polyester resin, and then subjected to tensile loads in order to obtain strength and deformability parameters, necessaries to assess the mechanical performance of the sensor packaging. For a specific package, an optimal curing condition has been found, showing good repeatability and adaptability for non-planar surfaces, such as occurs in rock engineering. The successfully packaged sensors and electrical strain gages were attached to standard rock specimens of gabbro. Longitudinal and transversal strains under compression loads were measured with both techniques, showing that response of FBG sensors is linear and reliable. An analytical model is used to characterize the influences of rock substrate and FBG packaging in strain transmission. As a result, we obtained a sensor packaging for non-planar and complex natural material under acceptable sensitivity suitable for very small strains as occurs in hard rocks.

A low-mass impact sensor for high-speed firmness sensing of fruits.

A low-mass impact sensor for high-speed firmness sensing of fruits was built and tested. Results of tests with a rubber ball indicated that the impact measurement was not sensitive to the distance between the impactor and the impacting surface of the sample within the range of 8 to 23 mm, and was not sensitive to how the sample was held. Tests with kiwifruits and peaches show good correlation between firmness readings obtained with the impact sensor and those obtained with the penetrometer. The best correlation was between the slope of the impact curve (at mid-point) and the force-deformation firmness. Preliminary test showed that the sensor could sense fruit firmness at a speed of 5 fruits/s.

The influence of sensor placement on in-situ ultrasound wave velocity measurement.

Ultrasound wave velocity was measured in 30 pieces of Spanish Scots pine (Pinus sylvestris L.), 90 x 140 mm in cross-section and 4 m long. Five different sensor placement arrangements were used: end to end (V0), face to opposite face, edge to opposite edge, face to same face and edge to same edge. The pieces were successively shortened to 3, 2 and 1 m, in order to obtain these velocities and their ratios to reference value V0 for different lengths and angles with respect to the piece axis for the crossed measurements. The velocity obtained in crossed measurements is lower than V0. A correction coefficient for crossed velocities is proposed, depending on the angle, to adjust them to the V0 benchmark. The velocities measured on a surface, are also lower than V0, and their ratio with respect to V0 is close to 0.97 for distances equal to or greater than 18 times the depth of the beam.

Development and Testing of a Fiber Bragg Grating Strain Sensor for Uniaxial Compression of Rock Specimens

Los sensores de fibra óptica son una tecnología que ha madurado en los últimos años, sin embargo, se requiere un mayor desarrollo de aplicaciones para materiales naturales como las rocas, que por ser agregados complejos pueden contener partículas minerales y fracturas de tamaño mucho mayor que las galgas eléctricas usadas tradicionalmente para medir deformaciones en las pruebas de laboratorio, ocasionando que los resultados obtenidos puedan ser no representativos. En este trabajo fueron diseñados, fabricados y probados sensores de deformación de gran área y forma curvada, usando redes de Bragg en fibra óptica (FBG) con el objetivo de obtener registros representativos en rocas que contienen minerales y estructuras de diversas composiciones, tamaños y direcciones. Se presenta el proceso de elaboración del transductor, su caracterización mecánica, su calibración y su evaluación en pruebas de compresión uniaxial en muestras de roca. Para verificar la eficiencia en la transmisión de la deformación de la roca al sensor una vez pegado, también fue realizado el análisis de la transferencia incluyendo los efectos del adhesivo, de la muestra y del transductor. Los resultados experimentales indican que el sensor desarrollado permite registro y transferencia de la deformación fiables, avance necesario para uso en rocas y otros materiales heterogénos, señalando una interesante perspectiva para aplicaciones sobre superficies irregulares, pues permite aumentar a voluntad el tamaño y forma del área de registro, posibilita también obtener mayor fiabilidad de resultados en muestras de pequeño tamaño y sugiere su conveniencia en obras, en las cuales los sistemas eléctricos tradicionales tienen limitaciones. ABSTRACT Optical fiber sensors are a technology that has matured in recent years, however, further development for rock applications is needed. Rocks contain mineral particles and features larger than electrical strain gauges traditionally used in laboratory tests, causing the results to be unrepresentative. In this work were designed, manufactured, and tested large area and curved shape strain gages, using fiber Bragg gratings in optical fiber (FBG) in order to obtain representative measurement on surface rocks samples containing minerals and structures of different compositions, sizes and directions. This reports presents the processes of manufacturing, mechanical characterization, calibration and evaluation under uniaxial compression tests on rock samples. To verify the efficiency of rock deformation transmitted to attached sensor, it was also performed the analysis of the strain transfer including the effects of the bonding, the sample and the transducer. The experimental results indicate that the developed sensor enables reliable measurements of the strain and its transmission from rock to sensor, appropriate for use in heterogeneous materials, pointing an interesting perspective for applications on irregular surfaces, allowing increasing at will the size and shape of the measurement area. This research suggests suitability of the optical strain gauge for real scale, where traditional electrical systems have demonstrated some limitations.