This PDF file contains the front matter associated with SPIE Proceedings Volume 8184, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

Automatic target recognition (ATR) has historically entailed the problems of detection, classification and tracking of ground or air targets from high resolution (imaging) sensor data as well as low resolution (radar) sensor data. A popular approach to solving the ATR problem is Bayesian inference, where detection (position and pose), classification and tracking are solved via a parameter estimation framework. The present paper offers a treatment of a subset of the aforementioned problem, which can be stated as "given imaging data of a stationary ground target and assuming that the target centroid's position is known in pixel coordinates, how can one estimate its pose (orientation) and class?" Furthermore, we also address the problem of scale invariance, i.e. how to ensure that, for instance, a target that appears smaller in an image is not misclassified to a class that has a similar sized template in the database? This problem is a very significant one since it is realistic to expect target templates in the database to be only of a certain size and of targets in the observed image to be smaller or larger depending on its relative distance to the camera. Hence, by proposing the use of scale as an additional parameter to be estimated, it is shown, via simulations, that this inclusion enhances the accuracy of class estimation.

The paper presents the test results of a mobile system for the protection of large-area objects, which consists of a radar and thermal and visual cameras. Radar is used for early detection and localization of an intruder and the cameras with narrow field of view are used for identification and tracking of a moving object. The range evaluation of an integrated system are presented as well as the probability of human detection as a function of the distance from radar-camera unit.

Next Generation EO/IR focal plane arrays using nanostructure materials are being developed for a variety of Defense Applications including Unattended Ground Sensor Applications. Several different nanomaterials are being evaluated for these applications. These include ZnO nanowires that have demonstrated large signal to noise ratio as a wide band gap nanostructure material in the UV band. Similarly, the work is under way using Carbon Nanotubes (CNT) for a high speed detector and focal plane array as bolometer for IR bands of interest, which can be implemented for the unattended ground sensor applications. In this paper, we will discuss the sensor design and model predicting performance of an EO/IR focal plane array that can cover the UV to IR bands of interest. The model can provide a robust means for comparing performance of the EO/IR FPA's and Sensors that can operate in the UV, Visible-NIR (0.4-1.8 μm), SWIR (2.0-2.5 μm), MWIR (3-5 μm), and LWIR bands (8-14 μm). This sensor model can be used as a tool for predicting performance of nanostructure arrays under development. We will also discuss our results on growth and characterization of ZnO/MgZnO nanowires and CNT's for the next generation sensor applications.

Multiple modalities sensor fusion has been widely employed in various surveillance and military applications. A variety of image fusion techniques including PCA, wavelet, curvelet and HSV has been proposed in recent years to improve human visual perception for object detection. One of the main challenges for visible and infrared image fusion is to automatically determine an optimal fusion strategy for different input scenes along with an acceptable computational cost. This paper, we propose a fast and adaptive feature selection based image fusion method to obtain high a contrast image from visible and infrared sensors for targets detection. At first, fuzzy c-means clustering is applied on the infrared image to highlight possible hotspot regions, which will be considered as potential targets' locations. After that, the region surrounding the target area is segmented as the background regions. Then image fusion is locally applied on the selected target and background regions by computing different linear combination of color components from registered visible and infrared images. After obtaining different fused images, histogram distributions are computed on these local fusion images as the fusion feature set. The variance ratio which is based on Linear Discriminative Analysis (LDA) measure is employed to sort the feature set and the most discriminative one is selected for the whole image fusion. As the feature selection is performed over time, the process will dynamically determine the most suitable feature for the image fusion in different scenes. Experiment is conducted on the OSU Color-Thermal database, and TNO Human Factor dataset. The fusion results indicate that our proposed method achieved a competitive performance compared with other fusion algorithms at a relatively low computational cost.

Accurate modeling of small firearms muzzle blast wave propagation in the far field is critical to predict sound pressure levels, impulse durations and rise times, as functions of propagation distance. Such a task being relevant to a number of military applications including the determination of human response to blast noise, gunfire detection and localization, and gun suppressor design. Herein, a time domain model to predict small arms fire muzzle blast wave propagation is introduced. The model implements a Friedlander wave with finite rise time which diverges spherically from the gun muzzle. Additionally, the effects in blast wave form of thermoviscous and molecular relaxational processes, which are associated with atmospheric absorption of sound were also incorporated in the model. Atmospheric absorption of blast waves is implemented using a time domain recursive formula obtained from numerical integration of corresponding differential equations using a Crank-Nicholson finite difference scheme. Theoretical predictions from our model were compared to previously recorded real world data of muzzle blast wave signatures obtained by shooting a set different sniper weapons of varying calibers. Recordings containing gunfire acoustical signatures were taken at distances between 100 and 600 meters from the gun muzzle. Results shows that predicted blast wave slope and exponential decay agrees well with measured data. Analysis also reveals the persistency of an oscillatory phenomenon after blast overpressure in the recorded wave forms.

Free-space optics (FSO) holds the potential for high bandwidth communication in situations where landline communication is not practical, with relatively low cost and maintenance. For FSO communication in maritime environments, laser beams propagating through the evaporation layer near the sea surface are affected by turbulence, the scattering coefficients of the water particles, and the salt water itself. To better gauge and understand the effects of turbulence on FSO communication, the refractive index structure parameter C²_n, which relates to scintillation strength, is determined from database of environmental parameters experimentally measured near the sea surface. A high speed Shack-Hartmann wavefront sensor is utilized to measure wavefront distortion of a beam transmitted though the evaporation layer, and thus determine the extent of turbulence encountered along the optical pathway. Through the use of adaptive optics, the wavefront of a transmitted beam is modulated in real time to compensate for turbulence, thereby providing optimal FSO reception. The Kalman filter method is also employed to reconstruct an original undistorted image from a series of sequential transmitted images altered by turbulence. In addition, atmospheric, free-space, and scintillation losses are analyzed and predicted for extended optical path lengths in view of their impact on FSO data transfer and communication. Furthermore, the effects of weather conditions on FSO transmission are investigated through MODTRAN based modeling at 1.55 μm wavelength, where multiple elevation angles are considered. Using advanced techniques, many limitations associated with infrared FSO transmission and reception in the evaporation layer may be overcome or circumvented.

5.625 Gbps bidirectional laser communication at 1064 nm has been demonstrated on a repeatable basis between a Tesat coherent laser communication terminal with a 6.5 cm diameter ground aperture mounted inside the European Space Agency Optical Ground Station dome at Izana, Tenerife and a similar space-based terminal (12.4 cm diameter aperture) on the Near-Field InfraRed Experiment (NFIRE) low-earth-orbiting spacecraft. Both night and day bidirectional links were demonstrated with the longest being 177 seconds in duration. Correlation with atmospheric models and preliminary atmospheric r₀ and scintillation measurements have been made for the conditions tested, suggesting that such coherent systems can be deployed successfully at still lower altitudes without resorting to the use of adaptive optics for compensation.

A free-space laser communication system has been designed and partially developed as an alternative to standard RF links from UAV to ground stations. This project belongs to the SINTONIA program (acronym in Spanish for low environmental-impact unmanned systems), led by BR&TE (Boeing Research and Technology Europe) with the purpose of boosting Spanish UAV technology. A MEMS-based modulating retroreflector has been proposed as a communication terminal onboard the UAV, allowing both the laser transmitter and the acquisition, tracking and pointing subsystems to be eliminated. This results in an important reduction of power, size and weight, moving the burden to the ground station. In the ground station, the ATP subsystem is based on a GPS-aided two-axis gimbal for tracking and coarse pointing, and a fast steering mirror for fine pointing. A beacon-based system has been designed, taking advantage of the retroreflector optical principle, in order to determine the position of the UAV in real-time. The system manages the laser power in an optimal way, based on a distance-dependent beam-divergence control and by creating two different optical paths within the same physical path using different states of polarization.

Beam steering is an enabling technology for establishment of ad hoc communication links, directed energy for infrared countermeasures, and other in-theater defense applications. The development of nonmechanical beam steering techniques is driven by requirements for low size, weight, and power, and high slew rate, among others. The predominant beam steering technology currently in use relies on gimbal mounts, which are relatively large, heavy, and slow, and furthermore create drag on the airframes to which they are mounted. Nonmechanical techniques for beam steering are currently being introduced or refined, such as those based on liquid crystal spatial light modulators; however, drawbacks inherent to some of these approaches include narrow field of regard, low speed operation, and low optical efficiency. An attractive method that we explore is based on optical phased arrays, which has the potential to overcome the aforementioned issues associated with other mechanical and nonmechanical beam steering techniques. The optical array phase locks a number of coherent optical emitters in addition to applying arbitrary phase profiles across the array, thereby synthesizing beam shapes that can be steered and utilized for a diverse range of applications.

The presentation is based in the research work carried out in EU funded project SGL for USaR (Second Generation Locator for Urban Search and Rescue Operations). The aim of this project is to develop wireless standalone communication system with embedded sensor network which can be globally used in rescue operations after accidents or terrorist attacks. The system should be able to operate without external support for several days: it should have autonomy with power supply and communication. The devices must be lightweight so that rescue team can easily carry them and finally they must be easy to install and use. The range of the wireless communication must cover an area of several square kilometers. The embedded sensor system must be able to detect sings of life but also detect hazards threatening the rescue operators thus preventing more accidents. It should also support positioning and digital mapping as well as the management of the search and rescue operation. This sensor network for urban search and rescue operations has been tested on a field conditions and it has proven to be robust and reliable and provides an energy efficient way of communication and positioning on harsh conditions.

Protecting critical infrastructure against intrusion, sabotage or vandalism is a task that requires a comprehensive situation picture. Modern security systems should provide a total solution including sensors, software, hardware, and a "control unit" to ensure complete security. Incorporating unmanned mobile sensors can significantly help to close information gaps and gain an ad hoc picture of areas where no pre-installed supervision infrastructure is available or damaged after an incident. Fraunhofer IOSB has developed the generic ground control station AMFIS which is capable of managing sensor data acquisition with all kinds of unattended stationary sensors, mobile ad hoc sensor networks, and mobile sensor platforms. The system is highly mobile and able to control various mobile platforms such as small UAVs (Unmanned Aerial Vehicles) and UGVs (Unmanned Ground Vehicles). In order to establish a real-time situation picture, also an image exploitation process is used. In this process, video frames from different sources (mainly from small UAVs) are georeferenced by means of a system of image registration methods. Relevant information can be obtained by a motion detection module. Thus, the image exploitation process can accelerate the situation assessment significantly.

Mobile sensor nodes hold great potential for collecting field data using fewer resources than human operators would require and potentially requiring fewer sensors than a fixed-position sensor array. It would be very beneficial to allow these mobile sensor nodes to operate unattended with a minimum of human intervention. In order to allow mobile sensor nodes to operate unattended in a field environment, it is imperative that they be capable of identifying and responding to external agents that may attempt to tamper with, damage or steal the mobile sensor nodes, while still performing their data collection mission. Potentially hostile external agents could include animals, other mobile sensor nodes, or humans. This work will focus on developing control policies to help enable a mobile sensor node to identify and avoid capture by a hostile un-mounted human. The work is developed in a simulation environment, and demonstrated using a non-holonomic, ground-based mobile sensor node. This work will be a preliminary step toward ensuring the cyber-physical security of ground-based mobile sensor nodes that operate unattended in potentially unfriendly environments.