The emergence of affordable practical miniature sensors has led to
a tremendous leap forward in the ability to conduct effective
Intelligence, Surveillance, and Reconnaissance (ISR) on the modern
battlefield. Sensors are now impressively small and are capable
of sensitively sensing many phenomena. Coupling this sensor data
with a real world coordinate often provides the best tactical
picture. However, it is not always practical to outfit these
sensors with Global Positioning System (GPS) receivers because of
size, weight and power (SWAP) limitations. It is very conceivable
that hundreds or thousands of these sensors could be randomly
distributed over a region, precluding careful placement at
specified locations. In this paper, we propose a method for not
only locating the individual sensors, but also subsequently using
the resulting sensor network as an alterative to GPS.
All objects and activities give off energy in some part of the spectrum, may leave tell-tail signs from their previous activities (e.g., earth scaring or vapor trails), or leave information about relationships that they may have with other entities and activities (e.g., networks). Many of these phenomenologies are either not picked up by current stovepiped sensors, or the data supplied by those sensors are not fully exploited to properly observe them. In either case, new sensor data as well as the better exploitation of existing data could be used to provide, or at least cross cue or correlate with other sensor data to detect, identify, geolocate or track different kind of problems. Current sensors are often designed for specific purposes and are capable of sensing only limited parts of the spectrum. Significantly broadening the sensing spectrum will be an essential element of solving the emerging class of new "hard problems". There are many other observables available that could be exploited to assist in that process. Thus one could broaden the sensing to observe those phenomenologies associated with combustion effluents; thermal radiation; magnetic anomalies; seismic movement; acoustics; unintended electromagnetic emissions, changing weather conditions, logistics support indicators, debris trails; impressed observables (such as tagging); and others. What's needed is a disciplined, analytical process that can map observables to sensors, and ultimately to mission utility. The process, described in this SPIE presentation will address a specific example on the flow from the establishment of requirements to prosecutable observables, to objectives, to identification of sensors and assets, to the allocation of sensors and assets to observables, all based on optimizing mission utility.
The ability to detect objects from image sequences and estimate their trajectory is useful in many applications like satellite tracking, missile guidance and interception. This paper proposes a reliable and an effective application for preventing loss of lives on event of airline crashes similar to the one on 9/11/2001. This contribution uses the MixeD algorithm for object detection, velocity estimation and the trajectory of the moving object in the spatiotemporal domain. The case study of the 9/11 event shows that the proposed method could have helped the authorities alert the people inside the towers far in advance about the hostile situation and could have saved a few more lives.
We are all sadly familiar with the suicide bombings that have been occurring overseas--and even closer to home, with the series of suicide attacks that occurred within the United States. These have so far been limited to perpetration by Muslim extremists who for the most part planned and executed their own attacks. This pattern has led to the creation of a "profile" for what we would expect a suicide attacker to be. However, as this mode of attack migrates toward the United States, this "profile," or signature, may alter. This paper discusses how some of these alterations may occur based on changes in modus operandi, and how they would manifest themselves in detectable forms within the Unites States.
Bioterrorism is no longer a hypothetical construct but a reality. Nevertheless, disease detection and intervention currently remain largely reliant on clinical assessment. Technology providing early detection of disease could impact the care of individual patients and the evolution of epidemic spread. Hyperspectral Imaging (HSI) is a remote sensing technology developed originally by the Department of Defense that combines high-resolution imaging with chemical spectroscopy. In other medical applications HSI is emerging as a new means of early or more sensitive detection of changes in tissue that can be used to define pathology, predict clinical outcomes and adapt therapy. As a small, robust, camera based, non-invasive device, HSI may be well suited to aid in defense against biological warfare or epidemic disease by providing early detection or confirmation of disease and by monitoring the efficacy of vaccination or therapy. Crossover applications exist in the evaluation and treatment of emerging diseases. HSI is well suited to be a screening tool to provide earlier or more accurate detection of disease in an at risk population to better treat and contain disease.
This paper analyzes the inherent contradictions that exist in most of the conventional approaches dealing with airplane hijacking, and presents a completely different approach, employing innovative technological and operational solution. The suggested techno-operational concept is derived from the Systematic Inventive Thinking (SIT) methodology which enforces the problem solver to search for a solution under a few constraining rules -- causing the solution (if found) to be very cost effective. The basic problem that arises from most existing conventional concepts is their very poor cost
effectiveness. Passengers, airport operators and aviation companies are all forced to invest on a continual basis, huge amounts of resources and time in order to prevent a hijacking event. The "Auto Immune" concept, discussed here, is based upon enlisting the passengers (in a case of "Hijacking Event" only) to foil the event successfully by releasing, in real-time, a very effective "One-time Non-Lethal Apparatus" (ONLA). This new paradigm changes dramatically the balance of power in favor of the "good guys", and the few hijackers will be neutralized at low risk to the passengers and
the aircraft. The detailed technological and operational concept is described, including: operation modes of ONLA, location, release method, safety issues, psychological and legal issues, etc.
In this paper we consider the problem of estimating chlorophyll content in vegetation using an experimental optical method from noisy spectral data. It is shown that the quantitative analysis of the spectral curves for the reflection of plant leaves may be the basis for development of new methods for interpretation of the data obtained by the remote measurement of plants. A mathematical model of vegetation reflectance is proposed to estimate the chlorophyll content from spectral data. Estimates are defined as minimizers of penalized cost functionals with sequential quadratic programming (SQR) methods. An estimation is related to the local scoring procedure for the generalized additive model. A deviation measurement in risk analysis of vegetation is considered. The role of deviation and risk measures in optimization is analyzed. Experimental and simulation results are shown for different agricultural plants using a functional-parametric representation of spectral curves.
The U.S. Geological Survey (USGS) EROS Data Center responds to emergencies on behalf of various government agencies for human-induced and natural disasters. This response consists of satellite tasking and acquisitions, satellite image registrations, disaster-extent maps analysis and creation, base image provision and support, web-based mapping services for product delivery, and post-disaster data archiving.
The emergency response staff are on call at all times and have access to many commercial and government satellite and aerial photography tasking authorities. They have access to data processing and photographic laboratory services for off-hour priority requests. They work with agencies for preparedness planning, which includes provision of base imagery. These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre-disaster data. These layers are incorporated into a web-based browser and data delivery service that is accessible either to the general public or to select customers. As usage declines, the data are moved to a post-disaster near-line archive that is still accessible, but not in real time.
Corporate, government and military bodies focus significant resources to develop sophisticated and capable information-based systems. The concept of people and resources connected by a robust network capable of extremely high rates of information exchange is very attractive because it allows smaller groups to coordinate together and focus effects from geographically diverse locations. However, there is also a hidden danger that comes with such advanced technology. For example, in the case of the U.S. Military, clearly United States holds a technological advantage over our adversaries and that this advantage is still expanding. This technology gap has resulted in the emergence of potent asymmetrical warfare. All too often in science fiction movies, we see a small group of humans defeat a technologically superior alien race by striking at a hidden weakness that renders all of their advanced weapons as useless, as a result of pervasive connectivity and interdependence. The analogy holds for any large network-centric enterprise, corporate or governmental. This paper focuses on specific technologies and methods that preempt this Achilles Heal scenario.
Previous work has suggested a potential value in the combination of physical property data types (e.g. magnetic and terrain slope) when searching for oil and mineral deposits. This work studies a notional multi-dimensional function to determine the likelihood of finding such deposits. Additionally, this hypothesis assumes some basic requirements must be meet in order to validate this function.
The standard for determining the value of commercially gathered electro optical imagery is the same as with any optical system -- the ability to determine object in the field of view. Further, this function is defined as the ability to determine the presence of two parallel lines, vice only one. The National Imagery and Mapping Agency (NIMA) uses a function called Digital Terrain Elevation Data (DTED) to determine the elevation within a field of view. The DTED values for each pixel within a digital, commercial image can be considered similar to a gradient, whereby higher values are merely higher elevations. For the commercial electro optical system IKONOS (owned by Space Imaging, Inc.), the “resolution” is commonly referred to as 1 meter, which is the least discernable, parallel-line, separation distance.
This hypothesis uses gravity and magnetic data to augment the DTED "gradient". As with the terrain values on the earth, gravity and magnetic values are continuously changing. Further, they can change for various reasons. Both are greatly affected by the changes in the subsurface materials, or the density of the soil and metallic content (e.g. iron). It is precisely these variations, through the combination of such differing forms of data, which can help determine the presence of oil and mineral deposits.
The core of this work is a notional function development. Previous peer review has rightly pointed out that data fusion principles state that data must be commensurable before it can be fused. This work does not attempt to redefine data fusion concepts, but merely establish a set of gradients for digital terrain, gravity, and magnetic data sets. From these gradients, a combined function is defined which relates to a unique "signatures" for oil and mineral deposits. This signature could be derived from common gradient data (DTED slope, gravity, and magnetic).