This short paper presents an overview of the theoretical and technological under-pinnings of D-Wave quantum annealing systems and surveys some methodological challenges that arise when benchmarking these highly unusual systems.
{"title":"Benchmarking D-Wave quantum annealing systems: some challenges","authors":"Catherine C. McGeoch","doi":"10.1117/12.2197731","DOIUrl":"https://doi.org/10.1117/12.2197731","url":null,"abstract":"This short paper presents an overview of the theoretical and technological under-pinnings of D-Wave quantum annealing systems and surveys some methodological challenges that arise when benchmarking these highly unusual systems.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121498841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The TNO Human Factors Search 2 dataset is a valuable resource for studies in target detection, providing researchers with observational data against which image-based target distinctness metrics and detection models can be tested. The observational data provided with the Search 2 dataset was created by human observers searching colour images projected from a slide projector. Many target distinctness metrics studies are however carried out not on colour images but on images that have been processed into greyscale by various means. This is usually done for ease of analysis and meaningful interpretation. Utility of a metric is usually assessed by analysing the correlation between metric results and recorded observational results. However, the question remains of how well the results from the contrast metrics analysed from monochromatic images could be expected to compare to the observational results from colour images. We present results of a photosimulation experiment conducted using a monochromatic representation of the Search 2 dataset and an analysis of several target distinctness metrics. The monochromatic images presented to observers were created by processing the Search 2 images into L*, a* and b* colour space representations, and presenting the L* (lightness) image. The results of this experiment are compared with the original Search 2 results, showing strong correlation (0.83) between the monochrome and colour experiments in terms of correct target detection, and in terms of search time. Target distinctness metrics from analysis of these images are compared to the results of the photosimulation experiments, and the original Search 2 results.
{"title":"Performance of target distinctness metrics evaluated against colour and monochromatic photosimulation results","authors":"Vivienne C. Wheaton, Joanne B. Culpepper","doi":"10.1117/12.2194229","DOIUrl":"https://doi.org/10.1117/12.2194229","url":null,"abstract":"The TNO Human Factors Search 2 dataset is a valuable resource for studies in target detection, providing researchers with observational data against which image-based target distinctness metrics and detection models can be tested. The observational data provided with the Search 2 dataset was created by human observers searching colour images projected from a slide projector. Many target distinctness metrics studies are however carried out not on colour images but on images that have been processed into greyscale by various means. This is usually done for ease of analysis and meaningful interpretation. Utility of a metric is usually assessed by analysing the correlation between metric results and recorded observational results. However, the question remains of how well the results from the contrast metrics analysed from monochromatic images could be expected to compare to the observational results from colour images. We present results of a photosimulation experiment conducted using a monochromatic representation of the Search 2 dataset and an analysis of several target distinctness metrics. The monochromatic images presented to observers were created by processing the Search 2 images into L*, a* and b* colour space representations, and presenting the L* (lightness) image. The results of this experiment are compared with the original Search 2 results, showing strong correlation (0.83) between the monochrome and colour experiments in terms of correct target detection, and in terms of search time. Target distinctness metrics from analysis of these images are compared to the results of the photosimulation experiments, and the original Search 2 results.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123215223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guidance of weapon systems relies on sensors to analyze targets signature. Defense weapon systems also need to detect then identify threats also using sensors. The sensors performance is very dependent on conditions e.g. time of day, atmospheric propagation, background ... Visible camera are very efficient for diurnal fine weather conditions, long wave infrared sensors for night vision, radar systems very efficient for seeing through atmosphere and/or foliage ... Besides, multi sensors systems, combining several collocated sensors with associated algorithms of fusion, provide better efficiency (typically for Enhanced Vision Systems). But these sophisticated systems are all the more difficult to conceive, assess and qualify. In that frame, multi sensors simulation is highly required. This paper focuses on multi sensors simulation tools. A first part makes a state of the Art of such simulation workbenches with a special focus on SE-Workbench. SEWorkbench is described with regards to infrared/EO sensors, millimeter waves sensors, active EO sensors and GNSS sensors. Then a general overview of simulation of targets and backgrounds signature objectives is presented, depending on the type of simulation required (parametric studies, open loop simulation, closed loop simulation, hybridization of SW simulation and HW ...). After the objective review, the paper presents some basic requirements for simulation implementation such as the deterministic behavior of simulation, mandatory to repeat it many times for parametric studies... Several technical topics are then discussed, such as the rendering technique (ray tracing vs. rasterization), the implementation (CPU vs. GP GPU) and the tradeoff between physical accuracy and performance of computation. Examples of results using SE-Workbench are showed and commented.
武器系统的制导依赖于传感器来分析目标的特征。国防武器系统也需要使用传感器来探测和识别威胁。传感器的性能非常依赖于条件，例如一天中的时间、大气传播、背景……可见光相机在白天晴朗的天气条件下非常有效，长波红外传感器用于夜视，雷达系统非常有效地穿透大气和/或树叶……此外，多传感器系统，结合多个并置传感器和相关的融合算法，提供更好的效率(通常用于增强视觉系统)。但这些复杂的系统更难构思、评估和鉴定。在这种情况下，多传感器仿真是非常必要的。本文主要研究多传感器仿真工具。第一部分介绍了这种仿真工作台的最新技术，特别关注SE-Workbench。SEWorkbench描述了红外/EO传感器、毫米波传感器、有源EO传感器和GNSS传感器。然后，根据所需的仿真类型(参数研究、开环仿真、闭环仿真、SW仿真和HW的混合……)，介绍了目标和背景签名目标仿真的总体概述。在客观回顾之后，本文提出了仿真实现的一些基本要求，如仿真的确定性行为，参数化研究必须多次重复仿真……然后讨论了几个技术主题，例如渲染技术(光线追踪vs.光栅化)，实现(CPU vs. GP GPU)以及物理精度和计算性能之间的权衡。展示了使用SE-Workbench的结果示例并进行了注释。
{"title":"Multisensors signature prediction workbench","authors":"J. Latger, T. Cathala","doi":"10.1117/12.2195052","DOIUrl":"https://doi.org/10.1117/12.2195052","url":null,"abstract":"Guidance of weapon systems relies on sensors to analyze targets signature. Defense weapon systems also need to detect then identify threats also using sensors. The sensors performance is very dependent on conditions e.g. time of day, atmospheric propagation, background ... Visible camera are very efficient for diurnal fine weather conditions, long wave infrared sensors for night vision, radar systems very efficient for seeing through atmosphere and/or foliage ... Besides, multi sensors systems, combining several collocated sensors with associated algorithms of fusion, provide better efficiency (typically for Enhanced Vision Systems). But these sophisticated systems are all the more difficult to conceive, assess and qualify. In that frame, multi sensors simulation is highly required. This paper focuses on multi sensors simulation tools. A first part makes a state of the Art of such simulation workbenches with a special focus on SE-Workbench. SEWorkbench is described with regards to infrared/EO sensors, millimeter waves sensors, active EO sensors and GNSS sensors. Then a general overview of simulation of targets and backgrounds signature objectives is presented, depending on the type of simulation required (parametric studies, open loop simulation, closed loop simulation, hybridization of SW simulation and HW ...). After the objective review, the paper presents some basic requirements for simulation implementation such as the deterministic behavior of simulation, mandatory to repeat it many times for parametric studies... Several technical topics are then discussed, such as the rendering technique (ray tracing vs. rasterization), the implementation (CPU vs. GP GPU) and the tradeoff between physical accuracy and performance of computation. Examples of results using SE-Workbench are showed and commented.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126754856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amplitude-phase errors and mutual coupling errors among multi-channels in digital array radar (DAR) will seriously deteriorate the performance of signal processing such as digital beam-forming (DBF) and high resolution direction finding. In this paper, a combined algorithm for error calibration in DAR has been demonstrated. The algorithm firstly estimates the amplitude-phase errors of each channel using interior calibration sources with the help of the calibration network. Then the signals from far field are received and the amplitude-phase errors are compensated. According to the subspace theories, the relationship between the principle eigenvectors and distorted steering vectors is expressed, and the cost function containing the mutual coupling matrix (MCM) and incident directions is established. Making use of the properties of MCM of uniform linear array, Gauss-Newton method is implied to iteratively compute the MCM and the direction of arrival (DOA). Simulation results have shown the effectiveness and performance of proposed algorithm. Based on an 8-elements DAR test-bed, experiments are carried out in anechoic chamber. The results illustrate that the algorithm is feasible in actual systems.
{"title":"Channel calibration for digital array radar in the presence of amplitude-phase and mutual coupling errors","authors":"Weixing Li, Yue Zhang, Jianzhi Lin, Zengping Chen","doi":"10.1117/12.2194626","DOIUrl":"https://doi.org/10.1117/12.2194626","url":null,"abstract":"Amplitude-phase errors and mutual coupling errors among multi-channels in digital array radar (DAR) will seriously deteriorate the performance of signal processing such as digital beam-forming (DBF) and high resolution direction finding. In this paper, a combined algorithm for error calibration in DAR has been demonstrated. The algorithm firstly estimates the amplitude-phase errors of each channel using interior calibration sources with the help of the calibration network. Then the signals from far field are received and the amplitude-phase errors are compensated. According to the subspace theories, the relationship between the principle eigenvectors and distorted steering vectors is expressed, and the cost function containing the mutual coupling matrix (MCM) and incident directions is established. Making use of the properties of MCM of uniform linear array, Gauss-Newton method is implied to iteratively compute the MCM and the direction of arrival (DOA). Simulation results have shown the effectiveness and performance of proposed algorithm. Based on an 8-elements DAR test-bed, experiments are carried out in anechoic chamber. The results illustrate that the algorithm is feasible in actual systems.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134540752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hyperspectral and multispectral imagery of shorelines collected from airborne and shipborne platforms are used following pushbroom imagery corrections using inertial motion motions units and augmented global positioning data and Kalman filtering. Corrected radiance or reflectance images are then used to optimize synthetic high spatial resolution spectral signatures resulting from an optimized data fusion process. The process demonstrated utilizes littoral zone features from imagery acquired in the Gulf of Mexico region. Shoreline imagery along the Banana River, Florida, is presented that utilizes a technique that makes use of numerically embedded targets in both higher spatial resolution multispectral images and lower spatial resolution hyperspectral imagery. The fusion process developed utilizes optimization procedures that include random selection of regions and pixels in the imagery, and minimizing the difference between the synthetic signatures and observed signatures. The optimized data fusion approach allows detection of spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using numerically embedded line targets within actual imagery. The approach allows one to test spectral signature anomaly detection and to identify features and targets. The optimized data fusion techniques and software allows one to perform sensitivity analysis and optimization in the singular value decomposition model building process and the 2-D Butterworth cutoff frequency and order numerical selection process. The data fusion “synthetic imagery” forms a basis for spectral-spatial resolution enhancement for optimal band selection and remote sensing algorithm development within “spectral anomaly areas”. Sensitivity analysis demonstrates the data fusion methodology is most sensitive to (a) the pixels and features used in the SVD model building process and (b) the 2-D Butterworth cutoff frequency optimized by application of K-S nonparametric test. The image fusion protocol is transferable to sensor data acquired from other platforms, including moving platforms as demonstrated.
{"title":"An approach to optimal hyperspectral and multispectral signature and image fusion for detecting hidden targets on shorelines","authors":"Charles R. Bostater","doi":"10.1117/12.2196293","DOIUrl":"https://doi.org/10.1117/12.2196293","url":null,"abstract":"Hyperspectral and multispectral imagery of shorelines collected from airborne and shipborne platforms are used following pushbroom imagery corrections using inertial motion motions units and augmented global positioning data and Kalman filtering. Corrected radiance or reflectance images are then used to optimize synthetic high spatial resolution spectral signatures resulting from an optimized data fusion process. The process demonstrated utilizes littoral zone features from imagery acquired in the Gulf of Mexico region. Shoreline imagery along the Banana River, Florida, is presented that utilizes a technique that makes use of numerically embedded targets in both higher spatial resolution multispectral images and lower spatial resolution hyperspectral imagery. The fusion process developed utilizes optimization procedures that include random selection of regions and pixels in the imagery, and minimizing the difference between the synthetic signatures and observed signatures. The optimized data fusion approach allows detection of spectral anomalies in the resolution enhanced data cubes. Spectral-spatial anomaly detection is demonstrated using numerically embedded line targets within actual imagery. The approach allows one to test spectral signature anomaly detection and to identify features and targets. The optimized data fusion techniques and software allows one to perform sensitivity analysis and optimization in the singular value decomposition model building process and the 2-D Butterworth cutoff frequency and order numerical selection process. The data fusion “synthetic imagery” forms a basis for spectral-spatial resolution enhancement for optimal band selection and remote sensing algorithm development within “spectral anomaly areas”. Sensitivity analysis demonstrates the data fusion methodology is most sensitive to (a) the pixels and features used in the SVD model building process and (b) the 2-D Butterworth cutoff frequency optimized by application of K-S nonparametric test. The image fusion protocol is transferable to sensor data acquired from other platforms, including moving platforms as demonstrated.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"9653 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130974432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a new approach, based on optical atomic magnetometers and magnetic induction tomography (MIT), for remote and non-invasive detection of conductive targets. Atomic magnetometers overcome the main limitations of conventional MIT instrumentation, in particular their poor low-frequency sensitivity, their large size and their limited scalability. Moreover, atomic magnetometers have been proven to reach extremely high sensitivities, with an improvement of up to 7 orders of magnitude in the 50 MHz to DC band, with respect to a standard pick-up coil of the same size. In the present scheme, an oscillating magnetic field induces eddy currents in a conductive target and laser-pumped atomic magnetometers, either stand-alone or in an array, detect the response of the objects. A phase-sensitive detection scheme rejects the background, allowing remote detection of the secondary field and, thus, mapping of objects, hidden in cargos, underwater or underground. The potential for extreme sensitivity, miniaturization, dynamic range and array operation paves the way to a new generation of non-invasive, active detectors for surveillance, as well as for real-time cargo screening.
{"title":"Magnetic induction imaging with optical atomic magnetometers: towards applications to screening and surveillance","authors":"L. Marmugi, S. Hussain, C. Deans, F. Renzoni","doi":"10.1117/12.2195482","DOIUrl":"https://doi.org/10.1117/12.2195482","url":null,"abstract":"We propose a new approach, based on optical atomic magnetometers and magnetic induction tomography (MIT), for remote and non-invasive detection of conductive targets. Atomic magnetometers overcome the main limitations of conventional MIT instrumentation, in particular their poor low-frequency sensitivity, their large size and their limited scalability. Moreover, atomic magnetometers have been proven to reach extremely high sensitivities, with an improvement of up to 7 orders of magnitude in the 50 MHz to DC band, with respect to a standard pick-up coil of the same size. In the present scheme, an oscillating magnetic field induces eddy currents in a conductive target and laser-pumped atomic magnetometers, either stand-alone or in an array, detect the response of the objects. A phase-sensitive detection scheme rejects the background, allowing remote detection of the secondary field and, thus, mapping of objects, hidden in cargos, underwater or underground. The potential for extreme sensitivity, miniaturization, dynamic range and array operation paves the way to a new generation of non-invasive, active detectors for surveillance, as well as for real-time cargo screening.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126654030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Active layers of bulk heterojunction are extensively studied because of their great potential for application in low-cost optoelectronic devices like photovoiltaic cells and photodiodes. The performance of such devices is strongly influenced by the formed nanostructures which determine the transport ability of the organic composite. We investigated the charge carrier transport properties of two organic composites: poly(3-hexyothiophene) (P3HT) with (6,6)-phenyl-C60-butyric acid methyl ester (60PCBM)and poly(triarylamine) (PTTA) blended with 60PCBM. The optimised organic blend was used as a matrix material for Cu-In-Se nanocrystals. Adding Cu–In–Se nanocrystals to a P3HT/60PCBM bulk heterojunction leads to a significant improvement of the maximum external quantum efficiency of the investigated system from 48% to 70% (at wavelength 520 nm).
{"title":"Hybrid organic-inorganic composites for applications in Vis-NIR photodiodes","authors":"B. Luszczynska, M. Z. Szymański","doi":"10.1117/12.2197481","DOIUrl":"https://doi.org/10.1117/12.2197481","url":null,"abstract":"Active layers of bulk heterojunction are extensively studied because of their great potential for application in low-cost optoelectronic devices like photovoiltaic cells and photodiodes. The performance of such devices is strongly influenced by the formed nanostructures which determine the transport ability of the organic composite. We investigated the charge carrier transport properties of two organic composites: poly(3-hexyothiophene) (P3HT) with (6,6)-phenyl-C60-butyric acid methyl ester (60PCBM)and poly(triarylamine) (PTTA) blended with 60PCBM. The optimised organic blend was used as a matrix material for Cu-In-Se nanocrystals. Adding Cu–In–Se nanocrystals to a P3HT/60PCBM bulk heterojunction leads to a significant improvement of the maximum external quantum efficiency of the investigated system from 48% to 70% (at wavelength 520 nm).","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"9 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114133811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
W. Gross, J. Boehler, H. Schilling, W. Middelmann, J. Weyermann, P. Wellig, R. Oechslin, M. Kneubuehler
Hyperspectral remote sensing data can be used for civil and military applications to detect and classify target objects that cannot be reliably separated using broadband sensors. The comparably low spatial resolution is compensated by the fact that small targets, even below image resolution, can still be classified. The goal of this paper is to determine the target size to spatial resolution ratio for successful classification of different target and background materials. Airborne hyperspectral data is used to simulate data with known mixture ratios and to estimate the detection threshold for given false alarm rates. The data was collected in July 2014 over Greding, Germany, using airborne aisaEAGLE and aisaHAWK hyperspectral sensors. On the ground, various target materials were placed on natural background. The targets were four quadratic molton patches with an edge length of 7 meters in the colors black, white, grey and green. Also, two different types of polyethylene (camouflage nets) with an edge length of approximately 5.5 meters were deployed. Synthetic data is generated from the original data using spectral mixtures. Target signatures are linearly combined with different background materials in specific ratios. The simulated mixtures are appended to the original data and the target areas are removed for evaluation. Commonly used classification algorithms, e.g. Matched Filtering, Adaptive Cosine Estimator are used to determine the detection limit. Fixed false alarm rates are employed to find and analyze certain regions where false alarms usually occur first. A combination of 18 targets and 12 backgrounds is analyzed for three VNIR and two SWIR data sets of the same area.
{"title":"Assessment of target detection limits in hyperspectral data","authors":"W. Gross, J. Boehler, H. Schilling, W. Middelmann, J. Weyermann, P. Wellig, R. Oechslin, M. Kneubuehler","doi":"10.1117/12.2192197","DOIUrl":"https://doi.org/10.1117/12.2192197","url":null,"abstract":"Hyperspectral remote sensing data can be used for civil and military applications to detect and classify target objects that cannot be reliably separated using broadband sensors. The comparably low spatial resolution is compensated by the fact that small targets, even below image resolution, can still be classified. The goal of this paper is to determine the target size to spatial resolution ratio for successful classification of different target and background materials. Airborne hyperspectral data is used to simulate data with known mixture ratios and to estimate the detection threshold for given false alarm rates. The data was collected in July 2014 over Greding, Germany, using airborne aisaEAGLE and aisaHAWK hyperspectral sensors. On the ground, various target materials were placed on natural background. The targets were four quadratic molton patches with an edge length of 7 meters in the colors black, white, grey and green. Also, two different types of polyethylene (camouflage nets) with an edge length of approximately 5.5 meters were deployed. Synthetic data is generated from the original data using spectral mixtures. Target signatures are linearly combined with different background materials in specific ratios. The simulated mixtures are appended to the original data and the target areas are removed for evaluation. Commonly used classification algorithms, e.g. Matched Filtering, Adaptive Cosine Estimator are used to determine the detection limit. Fixed false alarm rates are employed to find and analyze certain regions where false alarms usually occur first. A combination of 18 targets and 12 backgrounds is analyzed for three VNIR and two SWIR data sets of the same area.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114159518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Kilosanidze, G. Kakauridze, T. Kvernadze, Georgi Kurkhuli
An innovative real-time polarimetric method is presented based on the integral polarization-holographic diffraction element developed by us. This element is suggested to be used for real time analysis of the polarization state of light, to help highlight military equipment in a scene. In the process of diffraction, the element decomposes light incoming on them onto orthogonal circular and linear basis. The simultaneous measurement of the intensities of four diffracted beams by means of photodetectors and the appropriate software enable the polarization state of an analyzable light (all the four Stokes parameters) and its change to be obtained in real time. The element with photodetectors and software is a sensor of the polarization state. Such a sensor allows the point-by-point distribution of the polarization state in the images of objects to be determined. The spectral working range of such an element is 530 – 1600 nm. This sensor is compact, lightweight and relatively cheap, and it can be easily installed on any space and airborne platforms. It has no mechanically moving or electronically controlled elements. The speed of its operation is limited only by computer processing. Such a sensor is proposed to be use for the determination of the characteristics of the surface of objects at optical remote sensing by means of the determination of the distribution of the polarization state of light in the image of recognizable object and the dispersion of this distribution, which provides additional information while identifying an object. The possibility of detection of a useful signal of the predetermined polarization on a background of statistically random noise of an underlying surface is also possible. The application of the sensor is also considered for the nondestructive determination of the distribution of stressed state in different constructions based on the determination of the distribution of the polarization state of light reflected from the object under investigation. The prospect of this sensor application in astropolarymetry both for land and space telescopes is also discussed.
{"title":"Sensor for real-time determining the polarization state distribution in the object images","authors":"B. Kilosanidze, G. Kakauridze, T. Kvernadze, Georgi Kurkhuli","doi":"10.1117/12.2195078","DOIUrl":"https://doi.org/10.1117/12.2195078","url":null,"abstract":"An innovative real-time polarimetric method is presented based on the integral polarization-holographic diffraction element developed by us. This element is suggested to be used for real time analysis of the polarization state of light, to help highlight military equipment in a scene. In the process of diffraction, the element decomposes light incoming on them onto orthogonal circular and linear basis. The simultaneous measurement of the intensities of four diffracted beams by means of photodetectors and the appropriate software enable the polarization state of an analyzable light (all the four Stokes parameters) and its change to be obtained in real time. The element with photodetectors and software is a sensor of the polarization state. Such a sensor allows the point-by-point distribution of the polarization state in the images of objects to be determined. The spectral working range of such an element is 530 – 1600 nm. This sensor is compact, lightweight and relatively cheap, and it can be easily installed on any space and airborne platforms. It has no mechanically moving or electronically controlled elements. The speed of its operation is limited only by computer processing. Such a sensor is proposed to be use for the determination of the characteristics of the surface of objects at optical remote sensing by means of the determination of the distribution of the polarization state of light in the image of recognizable object and the dispersion of this distribution, which provides additional information while identifying an object. The possibility of detection of a useful signal of the predetermined polarization on a background of statistically random noise of an underlying surface is also possible. The application of the sensor is also considered for the nondestructive determination of the distribution of stressed state in different constructions based on the determination of the distribution of the polarization state of light reflected from the object under investigation. The prospect of this sensor application in astropolarymetry both for land and space telescopes is also discussed.","PeriodicalId":348143,"journal":{"name":"SPIE Security + Defence","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134371000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. K. Munk, O. T. Buus, J. Larsen, E. Dossi, Sol Tatlow, Lina Lässig, Lars Sandström, M. Jakobsen
Detection of illegal compounds requires a reliable, selective and sensitive detection device. The successful device features automated target acquisition, identification and signal processing. It is portable, fast, user friendly, sensitive, specific, and cost efficient. LEAs are in need of such technology. CRIM-TRACK is developing a sensing device based on these requirements. We engage highly skilled specialists from research institutions, industry, SMEs and LEAs and rely on a team of end users to benefit maximally from our prototypes. Currently we can detect minute quantities of drugs, explosives and precursors thereof in laboratory settings. Using colorimetric technology we have developed prototypes that employ disposable sensing chips. Ease of operation and intuitive sensor response are highly prioritized features that we implement as we gather data to feed into machine learning. With machine learning our ability to detect threat compounds amidst harmless substances improves. Different end users prefer their equipment optimized for their specific field. In an explosives-detecting scenario, the end user may prefer false positives over false negatives, while the opposite may be true in a drug-detecting scenario. Such decisions will be programmed to match user preference. Sensor output can be as detailed as the sensor allows. The user can be informed of the statistics behind the detection, identities of all detected substances, and quantities thereof. The response can also be simplified to “yes” vs. “no”. The technology under development in CRIM-TRACK will provide custom officers, police and other authorities with an effective tool to control trafficking of illegal drugs and drug precursors.
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