Search

During 2014 exceptionally warm water temperatures developed across a wide area off the California coast and within San Francisco Bay (SFB) and persisted through the middle of 2016. Observations and numerical model output are used to document this warming and its origins. The coastal warming was mostly confined to the upper 100 meters of the ocean and was manifested strongly in the two leading modes of upper ocean (0-100 m) temperature variability in the extra-tropical eastern Pacific. Observations in the suggest that the coastal warming in 2014 propagated into nearshore regions from the west and later indicate a warming influence that propagates from south to north into the region associated with the 2015-16 El Nino event. An analysis of the upper ocean (0-100 m) heat budget in a Regional Ocean Modeling System hindcast simulation confirmed this scenario. The results from a set of sensitivity runs with the model in which the lateral boundary conditions varied supports the conclusions drawn from the heat budget analysis. Concerning the warming in the SFB, an examination of the observations and the heat budget in an unstructured-grid numerical model simulation suggests that the warming during the second half of 2014 and early 2016 originates in the adjacent California coastal ocean and propagates through the Golden Gate into the Bay. The finding that the coastal and Bay warming are due to the relatively slow propagation of signals from remote sources raise the possibility that such warming events may be predictable several months in advance.

In this research, we focus on vessel detection using the satellite imagery of day/night band (DNB) on Suomi NPP in order to monitor the change of vessel activity on the region of South China Sea. In this paper, we consider the relation between the temporal change of vessel activities and the events on maritime environment based on the vessel traffic density estimation using DNB. DNB is a moderate resolution (350-700m) satellite imagery but can detect the fishing light of fishery boats in night time for every day. The advantage of DNB is the continuous monitoring on wide area compared to another vessel detection and locating system. However, DNB gave strong influence of cloud and lunar refection. Therefore, we additionally used Brightness Temperature at 3.7μm(BT3.7) for cloud information. In our previous research, we construct an empirical vessel detection model that based on the DNB contrast and the estimation of cloud condition using BT3.7. Moreover, we proposed a vessel traffic density estimation method based on empirical model. In this paper, we construct the time temporal density estimation map on South China Sea and East China Sea in order to extract the knowledge from vessel activities change.

Hyperspectral imaging (HSI) is a valuable tool for the detection and analysis of targets located within complex backgrounds. HSI can detect threat materials on environmental surfaces, where the concentration of the target of interest is often very low and is typically found within complex scenery. Unfortunately, current generation HSI systems have size, weight, and power limitations that prohibit their use for field-portable and/or real-time applications. Current generation systems commonly provide an inefficient area search rate, require close proximity to the target for screening, and/or are not capable of making real-time measurements. ChemImage Sensor Systems (CISS) is developing a variety of real-time, wide-field hyperspectral imaging systems that utilize shortwave infrared (SWIR) absorption and Raman spectroscopy. SWIR HSI sensors provide wide-area imagery with at or near real time detection speeds. Raman HSI sensors are being developed to overcome two obstacles present in standard Raman detection systems: slow area search rate (due to small laser spot sizes) and lack of eye-safety. SWIR HSI sensors have been integrated into mobile, robot based platforms and handheld variants for the detection of explosives and chemical warfare agents (CWAs). In addition, the fusion of these two technologies into a single system has shown the feasibility of using both techniques concurrently to provide higher probability of detection and lower false alarm rates. This paper will provide background on Raman and SWIR HSI, discuss the applications for these techniques, and provide an overview of novel CISS HSI sensors focusing on sensor design and detection results.

Light sheet fluorescent microscopy is able to provide high acquisition speed and high contrast images, as well as the low photo-bleaching and photo-damage brought to the sample. Here we describe a compact setup design optimized for applications in neuroscience, in particular fast imaging of sub-neuronal structures in mammalian brain slices. We report this prototype instrument is capable of rapid imaging wide area of the dendritic or axonal arbor of a dye-filled neuron in hippocampal slice. We also show several applications of this compact light sheet fluorescent microscope, to demonstrate that our approach offers a powerful functionality to the neuroscience community that is not achievable with traditional imaging methods.

Sensitive detection and rapid identification of hazardous bioorganic material with high sensitivity and specificity are essential topics for defense and security. A single method can hardly cover these requirements. While point sensors allow a highly specific identification, they only provide localized information and are comparatively slow. Laser based standoff systems allow almost real-time detection and classification of potentially hazardous material in a wide area and can provide information on how the aerosol may spread. The coupling of both methods may be a promising solution to optimize the acquisition and identification of hazardous substances. The capability of the outdoor LIF system at DLR Lampoldshausen test facility as an online classification tool has already been demonstrated. Here, we present promising data for further differentiation among bacteria. Bacteria species can express unique fluorescence spectra after excitation at 280 nm and 355 nm. Upon deactivation, the spectral features change depending on the deactivation method.

In recent years, PM2.5 air pollution is a social and transboundary environmental issue with the rapid economic growth in many countries. As PM2.5 is small and includes various ingredients, the detection of PM2.5 air pollutions by using satellite data is difficult compared with the detection of dust and sandstorms. In this paper, we examine various images (i.e., single-band images, band-difference images, RGB composite color images) to find a good method for detecting PM2.5 air pollutions by using MODIS data. A good method for the detection of PM2.5 air pollution is {R, G, B = band10, band9, T11}, where T11 is the brightness temperature of band31. In this composite color image, PM2.5 air pollutions are represented by light purple or pink color. This proposed method is simpler than the method by Nagatani et al. (2013), and is useful to grasp the distribution of PM2.5 air pollutions in the wide area (e.g., from China and India to Japan). By comparing AVI image with the image by proposed method, DSS and PM2.5 air pollutions can be classified.

It is becoming increasingly important in both the defence and security domains to conduct persistent wide area surveillance (PWAS) of large populations of targets. Wide Area Motion Imagery (WAMI) is a key technique for achieving this wide area surveillance. The recent development of multi-million pixel sensors has provided sensors with wide field of view replete with sufficient resolution for detection and tracking of objects of interest to be achieved across these extended areas of interest. WAMI sensors simultaneously provide high spatial and temporal resolutions, giving extreme pixel counts over large geographical areas. The high temporal resolution is required to enable effective tracking of targets. The provision of wide area coverage with high frame rates generates data deluge issues; these are especially profound if the sensor is mounted on an airborne platform, with finite data-link bandwidth and processing power that is constrained by size, weight and power (SWAP) limitations. These issues manifest themselves either as bottlenecks in the transmission of the imagery off-board or as latency in the time taken to analyse the data due to limited computational processing power.

Land subsidence is a common natural hazard striking extensive areas worldwide that can be triggered by geological and/or anthropogenic factors. In many cases, subsidence affects urbanized areas and causes remarkable economic loss. Adopted policies and solutions for land subsidence management can be various, but despite this variability, where mitigation methods have to be put into practice, the detailed mapping, characterization and simulation of subsidence have to precede their design and implementation. In the framework of the Terrafirma Project (www.terrafirma.eu.com), the exploitation of Persistent Scatterer Interferometry (PSI) for subsidence analysis has been promoted. Satellite interferometry, thanks to its wide spatial coverage and its millimeter accuracy, is ideally suited for the measurement of the spatial extent and magnitude of surface deformations associated with subsidence phenomena. Three validated case studies, where subsidence is caused by different factors, are presented here: the wide area of Rome (Italy), the Gioia Tauro plain (Italy) and the Kalochori village (Greece). These case studies have been selected with the aim of showing the main activities that must be covered and performed when dealing with geohazard investigations, i.e., mapping, monitoring and modeling. Particularly, data from ERS1/2, Envisat and Radarsat satellites have been exploited to map ground deformation in the area of Rome and to monitor the ground subsidence in the Gioia Tauro plain. Due to the large availability of geological and geotechnical data, the area of Kalochori village has been selected to model the land subsidence by applying Finite Element simulation. Results of the simulation have been validated with PSI techniques.

Wide area motion imagery (WAMI) has been attracting an increased amount of research attention due to its large spatial and temporal coverage. An important application includes moving target analysis, where vehicle detection is often one of the first steps before advanced activity analysis. While there exist many vehicle detection algorithms, a thorough evaluation of them on WAMI data still remains a challenge mainly due to the lack of an appropriate benchmark data set. In this paper, we address a research need by presenting a new benchmark for wide area motion imagery vehicle detection data. The WAMI benchmark is based on the recently available Wright-Patterson Air Force Base (WPAFB09) dataset and the Temple Resolved Uncertainty Target History (TRUTH) associated target annotation. Trajectory annotations were provided in the original release of the WPAFB09 dataset, but detailed vehicle annotations were not available with the dataset. In addition, annotations of static vehicles, e.g., in parking lots, are also not identified in the original release. Addressing these issues, we re-annotated the whole dataset with detailed information for each vehicle, including not only a target’s location, but also its pose and size. The annotated WAMI data set should be useful to community for a common benchmark to compare WAMI detection, tracking, and identification methods.

Automated analysis of wide area motion imagery (WAMI) can significantly reduce the effort required for converting data into reliable decisions. We register consecutive WAMI frames and use false-color frame comparisons to enhance the visual detection of possible subjects in the imagery. The large number of WAMI detections produces the need for a prioritization of detections for further inspection. We create a priority queue of detections for automated revisit with smaller field-ofview assets based on the locations of the movers as well as the probability of the detection. This automated queue works within an operator’s preset prioritizations but also allows the flexibility to dynamically respond to new events as well as incorporating additional information into the surveillance tasking.

In the last decade, there have been numerous developments in wide-area motion imagery (WAMI) from the sensor design to data exploitation. In this paper, we summarize the published literature on WAMI results in an effort to organize the techniques, discuss the developments, and determine the state-of-the-art. Using the organization of developments, we see the variations in approaches and relations to the data sets available. The literature summary provides and anthology of many of the developers in the last decade and their associated techniques. In our use case, we showcase current methods and products that enable future WAMI exploitation developments.

One of the desired capabilities for wide-area persistent ISR systems is to reliably locate and subsequently track the movement of targets within the field of view. Current wide-area persistent ISR systems are characterized by large pixel overall counts and very large fields of view. This leads to a large ground sample distance with few pixels-on-target. Locating targets under these constraints is extremely difficult due to the fact that the targets present very little detailed structure. In this paper we will present the application of rich image feature descriptors combined with advanced statistical target detection methodologies to the airborne ISR problem. We will demonstrate that these algorithms can reliably locate targets in the scene without relying on the target's motion to form a detection. This is useful in ISR application where it is desirable to be able to continuously track a target through stops and maneuvers.

Microbial biofilm is a colony of single bacteria cells (planktonic) that attached to surfaces, attract other microorganisms to attach and grow, and together they build an extracellular matrix composed of polysaccharides, protein, and DNA. Eventually, some cells will detach and spread to other surface. Biofilm on medical devices can cause severe infection to all age ranges from infant to adult. Therefore, it is important to detect biofilm in a fast and efficient manner. Hyperspectral imaging was utilized for distinguishing wide area of biofilm coverage on various materials and on different textures of stainless steeltest coupons. Not only is the coverage of biofilm important, but also the shear stress of biofilm on the attached surfaces is significant. This study investigates the effects of shear stress on the adhesion of biofilms on common medical device surfaces such as glass, polycarbonate, polytetrafluoroethylene, and stainless steel with different textures. Biofilm was grown using Ps. aeruginosa and growth was monitored after 24 and 48 hours at 37° C. The coupons covered with biofilm were tilted at 45 degrees and 90 degrees for 30 seconds to induce shear stress and Hyperspectral images were taken. We hypothesize that stronger attachment on rough surface would be able to withstand greater shear stress compared to smooth surface.

For quick detection of “open field” targets and landmines in tussock grass over wide area AMUSAR system must operate in low frequency below 500MHz and high frequency above 2.5GHz. The previous system calibration method used in AMUSAR adopts a compromise in single calibration object such as 0.1m trihedral. But for the frequency band between 500MHz and 1GHz, the 0.1m trihedral locates in Relay region with low signal-to-noise ratio (SNR). In order to improve performance of penetration, we make some modifications as follows. The data between 1GHz and 2.5GHz is calibrated by 0.1m trihedral. Since the 0.3m trihedral exhibits small fluctuation and large RCS between 500MHz and 1GHz, it ensures the SNR of calibration data. So the data is calibrated by 0.3m trihedral in this frequency band. The results show that the proposed method calibrates the system errors more efficiently and thus enhance the performance of imaging.

Defence Research and Development Canada – Atlantic (DRDC Atlantic) is currently involved in research on the topic of northern Maritime Domain Awareness (MDA). One project, entitled Situational Information for Enabling Development of Northern Awareness (SEDNA), includes research on the exploitation of MDA data in northern areas. One aspect of this research is to utilize wide area MDA data to provide awareness to an unattended, land-based system. Wide area MDA is attained through the use of space-based AIS (SAIS) data, a data feed used by the Canadian Department of National Defence and supplied by the commercial provider exactEarth Ltd. The land-based surveillance system used is the remote northern system constructed within the DRDC Northern Watch Technology Demonstration Project. Northern Watch is a multi-year project intended to show state-of-the-art, unattended, surveillance capabilities in the Canadian north. The link between the SAIS and Northern Watch is provided by a research infrastructure that consists of an assembly of data sources, users, applications, and product management techniques that collectively support research in areas such as information management and MDA data exploitation. High-level descriptions of the systems are provided along with elaboration on the alerting algorithm, the notifications that would be sent to the Northern Watch southern command site, and the resulting actions that could be taken by the Northern Watch surveillance system.

A standoff sensor called BioSense was developed to demonstrate the capacity to map, track and classify bioaerosol clouds from a distant range and over wide area. The concept of the system is based on a two steps dynamic surveillance: 1) cloud detection using an infrared (IR) scanning cloud mapper and 2) cloud classification based on a staring ultraviolet (UV) Laser Induced Fluorescence (LIF) interrogation. The system can be operated either in an automatic surveillance mode or using manual intervention. The automatic surveillance operation includes several steps: mission planning, sensor deployment, background monitoring, surveillance, cloud detection, classification and finally alarm generation based on the classification result. One of the main challenges is the classification step which relies on a spectrally resolved UV LIF signature library. The construction of this library relies currently on in-chamber releases of various materials that are simultaneously characterized with the standoff sensor and referenced with point sensors such as Aerodynamic Particle Sizer® (APS). The system was tested at three different locations in order to evaluate its capacity to operate in diverse types of surroundings and various environmental conditions. The system showed generally good performances even though the troubleshooting of the system was not completed before initiating the Test and Evaluation (T&E) process. The standoff system performances appeared to be highly dependent on the type of challenges, on the climatic conditions and on the period of day. The real-time results combined with the experience acquired during the 2012 T & E allowed to identify future ameliorations and investigation avenues.

We propose a method of using satellite images to analyze road conditions after a large-scale earthquake accompanied by a tsunami. Remote sensing using satellite images can be used to collect information over a wide area in a short time. Such information is particularly valuable for organizing relief efforts quickly and effectively after large-scale disasters such as the Great East Japan Earthquake on March 11, 2011. Although a large number of studies have focused on the extraction of damaged buildings and debris on roads, there have been few studies on the extraction of road areas flooded by a tsunami. Also, since the Great East Japan Earthquake, there has been increased concern about tsunami damage in addition to earthquake damage, meaning that a method of extracting both earthquake damage and tsunami damage is required. The purpose of this study is to analyze the safety of roads around a stricken area in detail to help support relief activities during times of disasters.

ScanSAR is an important imaging mode of operation for SAR systems. It allows extended range coverage albeit at the expense of azimuth resolution. Compared to stripmap, ScanSAR is used more for large swath coverage for mapping and monitoring over a wide area. Applications are numerous and include boreal forest mapping, wetland mapping and soil moisture monitoring. The goal of the present work was thus to explore the possibility of processing ScanSAR data optronicaly. Tests were performed with artificially bursted ASAR stripmap data demonstrating that reconstruction of ScanSAR data using the optronic SAR processor is feasible. This paper describes specifically how the data control and handling of ScanSAR data is performed to make it compatible with the optronic processor that was otherwise specifically designed for stripmap processing. As well, the ScanSAR images generated optronicaly are presented.

Threats associated with bioaerosol weapons have been around for several decades and have been mostly associated with terrorist activities or rogue nations. Up to the turn of the millennium, defence concepts against such menaces relied mainly on point or in-situ detection technologies. Over the last 10 years, significant efforts have been deployed by multiple countries to supplement the limited spatial coverage of a network of one or more point bio-detectors using lidar technology. The addition of such technology makes it possible to detect within seconds suspect aerosol clouds over area of several tens of square kilometers and track their trajectories. These additional capabilities are paramount in directing presumptive ID missions, mapping hazardous areas, establishing efficient counter-measures and supporting subsequent forensic investigations. In order to develop such capabilities, Defence Research and Development Canada (DRDC) and the Chemical, Biological, Radiological-Nuclear, and Explosives Research and Technology Initiative (CRTI) have supported two major demonstrations based on spectrally resolved Laser Induced Fluorescence (LIF) lidar: BioSense, aimed at defence military missions in wide open spaces, and SR-BioSpectra, aimed at surveillance of enclosed or semienclosed wide spaces common to defence and public security missions. This article first reviews briefly the modeling behind these demonstration concepts. Second, the lidar-adapted and the benchtop bioaerosol LIF chambers (BSL1), developed to challenge the constructed detection systems and to accelerate the population of the library of spectral LIF properties of bioaerosols and interferents of interest, will be described. Next, the most recent test and evaluation (T&E) results obtained with SR-BioSpectra and BioSense are reported. Finally, a brief discussion stating the way ahead for a complete defence suite is provided.

This article suggests the use of a cross-layer constraint (CLC), originated from the intrinsic relation between time slices of range-gated imaging Lidar, to facilitate the three-dimension contour reconstruction of the target. By using this physical-based method, both the effect of range ambiguity in the raw data and the dependence on the empirical image processing can be reduced, even when the Lidar system is operated on defocused state. Three outdoor scenes are fully studied to demonstrate the validity of CLC method, by using the data released by the push-broom range-gated imaging Lidar system newly developed for wide area depth mapping.

The increased prevalence of Closed Circuit Television systems has resulted in the necessity to view multiple simultaneous camera feeds. However in many cases, a single sensor unit with a wide field of view can ensure that the system operator's situational awareness can be greatly enhanced through the provision of a single continuous panoramic imaging system. This paper reports on advances that Waterfall Solutions Ltd (WS) has made in the field of wide area surveillance systems and introduces a low profile, wide field of view sensor system, and associated processing, which provides solutions to both of these problems.

Condition and growth of trees are considered to be important in monitoring global circulation with heat and water, additionally growth of trees are affected by CO 2 and air pollutants. On the other hand, since growth of plants is affected by surrounding climates, it is expected that real-time monitoring of crop plants growing makes possible quantitative agricultural management. This study proposed methods in measuring tree growth using hetero-core optical fiber sensors which are suitable for long-term, remote and real-time monitoring in wide area due to their features such as independence from temperature fluctuation and weather condition in addition to advantages of an optical fiber. Two types of sensors were used for that purpose. One of them was a dendrometer which measured radial changes of a tree stem and the other was elastic sensor which was to measure growth of smaller tree such as crop plant. In our experiment, it was demonstrated that the dendrometer was capable of measuring the differences of tree growing trend in period of different seasons such as growing rates 2.08 mm between spring and summer and 0.21 mm between autumn and winter, respectively. Additionally, this study had proposed the method of measuring crop plant growing by the elastic sensor because of its compact and light design and monotonious changes in optical loss to the amount of expansion and contraction.

Current trends in astronomical research necessitate a large number of small to medium sized telescopes be commissioned to support and augment the science goals of larger ground-based observatories and space observatories. The science mission requirements for these telescopes vary widely, yet the critical design requirements for the telescopes are largely consistent across many missions. This paper clarifies the critical functional and performance parameters of a gimbaled telescope system as dictated by three significant classes of telescope missions: laser transmission, wide area surveys and pointed surveys. Within these classifications several specific example science missions are considered from which specific telescope functional requirements are derived. Detailed telescope performance requirements are then evaluated from a systems engineering perspective, highlighting typical performance that may be expected from a modern telescope. Additional commentary is provided on the probable feasibility of upgrading older facilities in contrast to commissioning new telescopes systems. Based on the predictions of the NSF / NOAO sponsored ReSTAR report, it is assumed that the demand for highobservation- volume pointed surveys will increase rapidly within the next ten years. A case is made for the high science value of high gimbal slew rates on the basis of effective throughput in pointed survey applications.

In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

Recent experience has demonstrated that adversary activities are difficult to distinguish from background activity. In order to see hidden activities, it is proposed that a combination of new sensing modalities and better ways of processing existing modalities is required. We have applied a robust methodology to analyse the strengths and weaknesses of sensor types at detecting and characterising adversary activities. This has revealed both complementary and synergistic relationships between sensor types, supporting the hypothesis that judicious combining of data from multiple sensors will result in a sensing capability significantly greater than that achievable by individual sensors. The challenge to making this capability a reality is to develop and integrate automatic processing techniques to self-cue sensors and fuse their information, whilst avoiding additional burden on the users. To facilitate evolution and wide exploitation of this capability, we are developing an open, scalable architecture in which to integrate the sensors and processing. All of this work is now being taken forward in the UK's PWAS (Persistent Wide Area Surveillance) S2O demonstrator project which is working towards a rapid demonstration of the capability benefits of an integrated multiple sensor system. The immediate goal is to integrate mature equipment into a demonstrator system, as a test-bed for current and developing cueing/fusion processing algorithms. The near-term goal is to evolve the capability through technology updates which exploit new sensors and improved sensor processing.

Detecting humans and distinguishing them from natural fauna is an important issue in security applications to reduce false alarm rates. In particular, it is important to detect and classify people who are walking in remote locations and transmit back detections over extended periods at a low cost and with minimal maintenance. The ability to discriminate men versus animals and vehicles at long range would give a distinct sensor advantage. The reduction in false positive detections due to animals would increase the usefulness of detections, while dismount identification could reduce friendly-fire. We developed and demonstrate a compact radar technology that is scalable to a variety of ultra-lightweight and low-power platforms for wide area persistent surveillance as an unattended, unmanned, and man-portable ground sensor. The radar uses micro-Doppler processing to characterize the tracks of moving targets and to then eliminate unimportant detections due to animals or civilian activity. This paper presents the system and data on humans, vehicles, and animals at multiple angles and directions of motion, demonstrates the signal processing approach that makes the targets visually recognizable, and verifies that the UGS radar has enough micro-Doppler capability to distinguish between humans, vehicles, and animals.

This paper addresses multi-sensor surveillance where some sensors provide intermittent, feature-rich information. Effective exploitation of this information in a multi-hypothesis tracking context requires computationally-intractable processing with deep hypothesis trees. This report introduces two approaches to address this problem, and compares these to single-stage, track-while-fuse processing. The first is a track-before-fuse approach that provides computational efficiency at the cost of reduced track continuity; the second is a track-break-fuse approach that is computationally efficient without sacrificing track continuity. Simulation and sea trial results are provided.

We describe a real-time wide area surveillance system (WA-ACTV) for the automatic tracking of vessels using a network of PTZ cameras. The system is capable of optimally managing hundreds of PTZ cameras to simultaneously track a large numbers of vessels. The tracked vessels are fingerprinted using a scale-invariant part-based representation and subsequently used for reacquiring the tracks when the vessel comes back into view on a different sensor thus allowing the system to extend the tracking range over the wide area of surveillance. We have realized a small-scale version of the system and demonstrated it in an inland waterway as well as a small section of a sea port. The system operates in real-time at a frame rate of 15 Hz and is easily scalable to hundreds of PTZ cameras. The fingerprint-based reacquisition of targets has been evaluated to have a accuracy of 91%.

in many regions of the globe an update knowledge of the snow cover extent and wetness is of primary importance for both scientific and application aspects. Indeed, snow plays a major role in the global water cycle and the climate system, as well as in natural disasters such as floods, landslides. An operational algorithm to produce snow cover maps from remote sensing data in the Italian Alps has been implemented in the framework of the Italian national project PROSA to contribute timely information to civil protection from floods and landslides. The algorithm can generate maps in presence of cloud cover by combining optical data from MODIS and SAR data from ENVISAT. It has been validated on a wide area in North Italy by comparing the algorithm output with ground measurements. © 2009 SPIE.

This paper describes the NATO Task Group SET-093/RTG53/MSE (referred to as TG-53 in this report) Acoustic Detection of Weapons Firing Joint Field Experiment II conducted at the Etablissement Technique de Bourges (ETBS), Bourges, France, during 16 to 27 June 2008. This field experiment is a follow-on to the NATO TG-53 Acoustic Detection of Weapons Firing Joint Field Experiment I conducted at the Yuma Proving Grounds (YPG), Yuma, Arizona, USA, during 31 October to 4 November 2005 [1]. The objectives of the joint experiment were: (i) to collect acoustic signatures of direct and indirect firings from weapons' such as small arms, mortars, artillery, rockets, and C4 explosives, (ii) to analyze the propagation effects of grassy, wooded, and urban terrains, (iii) to share signatures collected from a variety of acoustic sensors, on the ground and in the air, distributed over a wide area, and (iv) to demonstrate the interoperability of disparate sensors developed by the various nations involved. The participating NATO countries , including France, the Netherlands, the United Kingdom, Canada, and the United States of America, and Israel as well as part of the Mediterranean dialogue countries, deployed nearly 90 sensors and sensor systems over the test range area.

Finding, tracking and monitoring events and activities of interest on a continuous basis remains one of our highest Intelligence Surveillance and Reconnaissance (ISR) requirements. Unmanned Aerial Systems (UAS) serve as one of the warfighter's primary and most responsive means for surveillance and gathering intelligence information and are becoming vital assets in military operations. This is demonstrated by their significant use in Afghanistan during Operation Enduring Freedom and in Iraq as part of Operation Iraqi Freedom. Lessons learned from these operations indicate that UAVs provide critical capabilities for enhancing situational awareness, intelligence gathering and force protection for our military forces. Current UAS high resolution electro-optics offers a small high resolution field of view (FOV). This narrow FOV is a limiting factor on the utility of the EO system. The UAS that are available offer persistence; however, the effectiveness of the EO system is limited by the sensors and available processing. DARPA is addressing this developing the next generation of persistent, very wide area surveillance with the Autonomous Real-time Ground Ubiquitous Surveillance - Imaging System (ARGUS-IS). The system will be capable of imaging an area of greater than 40 square kilometers with a Ground Space Distance (GSD) of 15 cm at video rates of greater than 12 Hz. This paper will discuss the elements of the ARGUS-IS program.

The gases accumulated inside the landfill as result of the fermentation of Municipal Solid Waste (MSW) known as biogas, are taking into consideration all possible uses as direct transformation into electricity. The system for collecting, regulating and controlling the biogas must include all the necessary safety features where the biogas leakage presents a high impact. Infrared thermography can be use to detect gas leakages due to the differences in temperature between the gas and the immediate surroundings. This method is able to monitor a wide area of landfill sites, quickly. This technology will not be effective if the differences in temperature are not better than five degrees. This paper describes a field test conducted to study the limitations of the infrared thermography caused by weather conditions and the moment of day or/and season when the thermal images was captured. Pipelines, borders, cells, covers, slopes and leakage (hot spots) are studied and optimum conditions are defined.

In this paper, we discuss the NATO Task Group 53 (TG-53) acoustic detection of weapon firing field joint experiment at Yuma Proving Ground during 31 October to 4 November 2005. The participating NATO countries include France, the Netherlands, UK and US. The objectives of the joint experiments are: (i) to collect acoustic signatures of direct and indirect firings from weapons such as sniper, mortar, artillery and C4 explosives and (ii) to share signatures among NATO partners from a variety of acoustic sensing platforms on the ground and in the air distributed over a wide area.

We have developed 3D-Measuring-Modelling System, which can be applied to any object from small to large size, using a note PC and digital cameras. This time, especially in view of its application to the area of industrial measurement, we have endeavored to attain higher accuracy in 3D measurement (from former 0.26mm to present below 0.1mm) as well as the further simplification of the measuring operation. For this purpose we have developed a scale bar and other peripheral devices and we assessed the resulted accuracy. Therefore, today we should like to report on the new system thus developed and its accuracy assessment, as well as its various application examples in automobile measurement.

Conventional metal detectors require people to walk through a door-like opening that houses the detection system. Typically, each person must be scanned individually. This creates a “choke point,” and long lines form at the screening point. This paper describes a metal detection sensor system that could screen large crowds of people more efficiently. The new system is called the Wide-Area Metal Detection (WAMD) sensor system. This sensor system is composed of a spatially distributed metal detector and a video surveillance system. The sensor system is designed to continually screen an area and reduce the need for each person to be examined separately.

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time that any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.

changed substantially and that surveillance systems designed to operate against heavy armor following conventional tactics have to adapt to a “New Threat” environment. This observation is very pertinent to the use of acoustic and seismic sensors. These sensing modalities have been used with success against a threat consisting of armored vehicles powered by large Diesel engines. In the type of conflicts that we are likely to encounter in places like Afghanistan, Yemen and other SE Asian countries, US forces will be faced by a threat that can move about in converted civilian vehicles, Figure 1. Systems like the Wide Area Mine (a.k.a. Hornet) and the Brilliant Anti-Tank Munition (BAT) exploited the loud and distinctive signatures of combat vehicles to direct their fire control system. Other surveillance systems such as Steel Rattler / Steel Eagle and DARPA’s Micro-IUGS focused on “high value targets”, also military vehicles of considerable size. All of these target vehicles are powered by large, noisy diesel engines and have large tires or tracks that produce substantial seismic signatures.The object of this paper is to present an analysis of the signatures of civilian vehicles that may be adapted to military or terrorist activities. We will then look at the sensor configurations that are best adapted to detect and track these vehicles. Some examples of the type of surveillance data that we can obtain are also shown in the paper.

With the advent of hyperspectral imaging spectrometers comes the need for procedures that detect and interrogate spectral quantities of interest. Such procedures or algorithms play a key role in the dissemination and interpretation of hyperspectral data. Validation of these algorithms involves well-characterized field collection campaigns that can be time and cost prohibitive. Radiometrically, as well as geometrically, correct synthetic imagery offers algorithm developers a surrogate to potentially unattainable field campaigns. The image simulation surrogate must ideally match real world scenes in both spatial and spectral complexity for one to have faith in algorithm performance. To this end, there is a need to develop synthetic scenes, based on real world data, which encompass full 3-dimensional geometric complexities as well as wide-area, spectrally complex backgrounds. Prior work has been done on the inclusion of backgrounds into a synthetic environment, however, this work did not generate wide-area imagery with all the complexities realized in real world data. This paper investigates the generation of a wide area synthetic scene rendered by the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The large area scene or "MegaScene" described in this paper is 0.6 square miles and contains an order of magnitude increase in objects, materials, and spectra, as compared to previously rendered scenes. Hyperspectral analysis using off-the-shelf classification and target detection algorithms was performed on the data to illustrate quantitative and qualitative fidelity.

The replacement of chemical batteries with composite flywheels offers many potential advantages in space applications. Before such flywheels can be successfully employed, it is imperative to ensure their integrity using NDE techniques. Previously, the use of traditional C-scan for the NDE of flywheels was compared to Scanning Ultrasonic Spectroscopy. However, both C-scan and scanning ultrasonic spectroscopy are point-by-point inspection techniques, and are thus inherently limited in inspection speed. In this paper, the application of Acoustography for the NDE of flywheels is reported. Acoustography provides an efficient and economical alternative to point-by-point ultrasonic scanning; in this approach a novel, wide area (AO) sensor is employed to provide full-field, real time ultrasonic images similar to x-ray imaging, significantly decreasing the required inspection time. Side by side images generated using Acoustography and traditional C-scan techniques for Plexiglas cylinder and a composite ring standard (both with known defects) are presented.

The following paper describes a recent data collection exercise in which the WAR HORSE visible-near-infrared hyperspectral sensor was employed in the collection of wide- area hyperspectral data sets. Two anomaly detection algorithms, Subspace RX (SSRX) ans Gaussian Spectral Clustering (GSC), were used on the data and their performance is discussed.

Tele-medical imaging applications require low cost, and high-speed backbone wide area networks (WAN) to carry large amount of imaging data for rapid turn around interpretation. Current low cost commercially WAN is too slow for medical imaging applications, while high speed WAN is too costly. The next generation Internet (NGI) or Internet2 is federal initiatives for the integration of higher speed backbone communication networks (up to 2.4 Gbits/sec) as a means to replace the current inadequate Internet for many applications including medical imaging. This paper describes our preliminary experience of connecting to Internet2 for teleradiology application. A case study is given for the NGI WAN connection between Childrens Hospital Los Angeles and National Library of Medicine. NGI WAN performance for different image modalities, measured in throughput rate and application response time, were obtained and then compared to the T1 WAN connection between Childrens Hospital Los Angeles and Saint John's Health Center Santa Monica.

A principal components (PC)-based transformation was previously introduced for mapping high-dimensional hyperspectral imagery (HSI) into 3-dimensional colorimetric displays [Tyo, Diersen, and Olsen, SPIE vol. 4132, Descour and Shen, Eds., 2001, pp. 147-156]. In this study, the previous work is extended to examine the conical nature of HSI data in the PC-based space. Picturing the data as conical provides insight as to the location of the origin of the cone (which might not be included in the data) and the point of shade. Once the origin of the cone is located, the PC-based color transformation is more stable with respect to hue constancy. Strategies are introduced to make the method invariant, i.e. to ensure that important scene constituents appear with consistent and intuitive presentations.

Acoustography is a full field, large area ultrasonic imaging method where a novel, wide area acousto-optic (AO) sensor is employed to form ultrasonic images similarly to real-time x-ray imaging. The AO sensor converts ultrasound directly into a visual image due to the inherent acousto-optic property of a proprietary mesophase material contained in the AO sensor. The AO sensor also offers exceptionally high pixel resolution, as a continuous layer of the mesophase material, with sensing molecules on the order of 20 Angstroms in size, senses the ultrasound. This paper will report on progress being made under a SBIR project to develop acoustography as an efficient and economical alternative to conventional point-by-point ultrasonic scanning (e.g. A-scan, C-scan).

Military and commercial aircraft structures are being fielded well beyond their designed life cycle, resulting in escalating maintenance costs. The principle driver behind these costs is the need to nondestructively interrogate large areas to detect and quantify anomalies such as corrosion, cracks, and delaminations. Manual ultrasonic techniques are routinely applied to inspect aircraft structures, but these techniques are time consuming, laborious, and are prone to errors such as operator fatigue and subjectivity. Automated ultrasonic systems require costly, complex scanning systems that are often difficult to adapt to complex shaped structures. Acoustography can provide full-field ultrasonic images in near real-time, making it a suitable method for high-speed, wide area inspection applications. This paper will report on progress being made toward developing acoustography for NDE of aging aircraft structures.

In these paper the selected physical processes of interaction of laser beams with biological tissues are presented. From the wide area of medical applications of laser systems three very interesting problems are presented: medical application of pulsed lasers sources (from some hundred of microseconds to femtoseconds of laser pulse duration), the physical processes accompanied with an interaction of laser beams in spectral range 2000-3000nm, and the selected methods of optical diagnostics of a human tissues parameters. The fundamental scientific, technical, and construction problems of novel laser systems for medical applications are presented. These problems are illustrated by the results of the clinical and laboratory experiments.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The objective of this study is to provide details on a novel wide area acousto-optic (AO) sensor that can be used to nondestructively evaluate materials and components in near real-time. A description of the technology and how it compares to conventional ultrasonic methods is provided. The results from three experiments provide details on how acoustography compares to conventional ultrasonics when applied to the inspection of composite parts. The first experiment involves performing ultrasonic and acoustography tests on a standard graphite/epoxy composite panel that has embedded inclusions of known sizes. The objective of this experiment is to determine if the capabilities (i.e. resolution) of acoustography are comparable to those of conventional ultrasonic techniques. The second experiment applied acoustography and ultrasonic techniques to evaluate the effects of low impact damage in composite materials. The third experiment involves applying ultrasonics and acoustography to evaluate a complex shaped composite part. The purpose of this experiment is to show the strengths and weaknesses of both techniques as applied to real world problems.

This communication introduces the Optics and Signal Processing Group from (Jni'.'ersidad industrial d' Saniandcr at Bucaramanga. Colombia. First, a brief description of how the group was formed, its strategic importance and also some of its more important achievements are presented. Then, the main scientific domains where the group carries out its research are described and fmally, some guidelines about future research work in the group are given.Keywords: research works in optics of Colombia, hybrid signal processing, optics metrology and optics with photorefractivematerials. 1. INTRODUCTIONThe Universidad Industrial de Santander (UIS), considered one of the five more important public universities of Colombia for half a century it has contributed to the development of a wide area of the Colombian northeast, offering highlevel education for engineers and scientists. Optics at UIS started by 1972. when the graduated physics department was created. Thanks to an agreement with the French embassy, the

The polarization corrected temperature (PCT) derived from SSM/I 85 GHz data is used for the retrieval of rainfall rate over South China in the summer season. The 85 GHz PCT observed from space is strongly dependent on the emission and scattering by cloud and rain droplet particles. Hourly rain gauge measurement data were used to relate PCT with surface rainfall rate. Since the rainfall phenomena have large variabilities in time and space, a direct comparison between rain gauge measurement and satellite measurement is not adequate. On the other hand the rainfall rate distribution in a wide area does not change even if the measurement time is slightly different. Therefore the rainfall rate distribution measured with rain gauge and PCT change distribution were compared and a relationship between them is constructed. By applying it to SSM/I data, rainfall properties over the South China during periods from June to August of 1991-1995 were investigated.

In a wide area WDM network with a huge capacity, dispersion limits the scope of the network. Among new ideas of dispersion compensation, dispersion compensation fiber (DCF) is the best. However, DCF can not balance the dispersion of all channels because of dispersion slope. There is surplus dispersion in some channels, so that further compensation of the surplus dispersion is needed after the using of DCF. The FP resonator is a dispersion-tunable device. The surplus dispersions of all the channels can be compensated after the suing of FP resonator as a tunable receiver. The numerical results show that the radius of WDm network can be made three times as large as it would have been without this device.

Three dimensional visualization of tumor and normal tissues are often valuable in precision treatment planning for radiation therapy of cancer. This is often not possible in many remote treatment facilities because of the high cost of imaging and computer equipment. At the University of Southern California, School of Medicine we are developing and testing a high speed, wide area, computer communications network to provide access to such resources from remote locations. In this paper, we present our concept of a Virtual Academic Medical Center, our network design and report on initial evaluations of effectiveness and clinical acceptability of 3D, CT simulation and treatment planning from a distance.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.