This PDF file contains the front matter associated with SPIE Proceedings Volume 6736, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

TARDEC has been developing payloads for small robots as part of its unmanned ground vehicle (UGV) development programs. These platforms typically weigh less than 100 lbs and are used for various physical security and force protection applications. This paper will address a number of technical issues including platform mobility, payload positioning, sensor configuration and operational tradeoffs. TARDEC has developed a number of robots with different mobility mechanisms including track, wheel and hybrid track/wheel running gear configurations. An extensive discussion will focus upon omni-directional vehicle (ODV) platforms with enhanced intrinsic mobility for positioning sensor payloads. This paper also discusses tradeoffs between intrinsic platform mobility and articulated arm complexity for end point positioning of modular sensor packages.

This paper describes recent efforts to develop integrated multi-sensor payloads for small robotic platforms for improved operator situational awareness and ultimately for greater robot autonomy. The focus is on enhancements to perception through integration of electro-optic, acoustic, and other sensors for navigation and inspection. The goals are to provide easier control and operation of the robot through fusion of multiple sensor outputs, to improve interoperability of the sensor payload package across multiple platforms through the use of open standards and architectures, and to reduce integration costs by embedded sensor data processing and fusion within the sensor payload package. The solutions investigated in this project to be discussed include: improved capture, processing and display of sensor data from multiple, non-commensurate sensors; an extensible architecture to support plug and play of integrated sensor packages; built-in health, power and system status monitoring using embedded diagnostics/prognostics; sensor payload integration into standard product forms for optimized size, weight and power; and the use of the open Joint Architecture for Unmanned Systems (JAUS)/ Society of Automotive Engineers (SAE) AS-4 interoperability standard. This project is in its first of three years. This paper will discuss the applicability of each of the solutions in terms of its projected impact to reducing operational time for the robot and teleoperator.

There has been an increasing interest of unmanned vehicles keeping the importance of defense and security. A few models for a convoy of unmanned vehicle exist in literature. The objective of this paper is to exploit agent based modeling technique for a convoy of unmanned vehicles where each vehicle is an agent. Using this approach, the convoy of vehicles reaches a specified goal from a starting point. Each agent is associated with number of sensors. The agents make intelligent decisions based on sensor inputs and at the same time maintaining their group capability and behavior. The simulation is done for a battlefield environment from a single starting point to a single goal. This approach can be extended for multiple starting points to reach multiple goals. The simulation gives the time taken by the convoy to reach a goal from its initial position. In the battlefield environment, commanders make various tactical decisions depending upon the location of an enemy outpost, minefields, number of soldiers in platoons, and barriers. The simulation can help the commander to make effective decisions depending on battlefield, convoy and obstacles to reach a particular goal. The paper describes the proposed approach and gives the simulation results. The paper also gives problems for future research in this area.

There is an increasing interest in the use of a convoy of unmanned intelligent vehicles for defense and security. These vehicles have a number of sensors associated with them. It is very important to have a highly reliable sensor network so as to determine the dynamic reliability of the intelligent vehicle system for a safe battlefield environment. The mobility, path planning and navigation of such convoy of vehicles are in the state of infancy. However, it is considered important to develop the reliability techniques so that a commander in the battle of field can predict the reliability of the various stages of the movement of the convoy. He can then take decisions depending on reliabilities determined at various places and time. In this paper a combination of intelligent techniques like fuzzy and Boolean algebra techniques are exploited to determine the reliability of the network in the battlefield. The branches of reliabilities are determined using intelligent approaches like fuzzy logic while terminal reliabilities are determined using Boolean algebra. Based on this approach, a new algorithm is proposed in determining the dynamic reliability of convoy of unmanned intelligent vehicles. Such an approach will help in the collaboration and coordination of the convoy of vehicles.

The nature of co-operating Uninhabited Vehicle (UV) systems is such that performance enhancements are likely to be a result of greatly increased system complexity. Complexity emerges through the interaction of multiple autonomous UVs reacting to their current surroundings. This complexity presents a fundamental challenge to the specification, design and evaluation of such systems, and drives the need for new approaches to the systems engineering. For applications involving multiple autonomous UVs, research into collective and emergent behaviour offers potential benefits in terms of improved system performance and the utilisation of individual UVs with lower processing complexity. This paper reports on the development of a new simulation framework that addresses the systems engineering issues and allows novel algorithms to be created and assessed. Examples are given of how the framework has been used to develop and assess the performance of individual and multiple UVs, as well as unattended ground sensors. Furthermore, a variety of novel algorithms developed using the framework are described and example results are provided. These include co-operative UV missions requiring improved detection performance and the improved management of unattended ground sensors to minimise power usage.

Proposed are techniques toward using collaborative robots for infrastructure security applications by utilizing them for mobile sensor suites. A vast number of critical facilities/technologies must be protected against unauthorized intruders. Employing a team of mobile robots working cooperatively can alleviate valuable human resources. Addressed are the technical challenges for multi-robot teams in security applications and the implementation of multi-robot motion planning algorithm based on the patrolling and threat response scenario. A neural network based methodology is exploited to plan a patrolling path with complete coverage. Also described is a proof-of-principle experimental setup with a group of Pioneer 3-AT and Centibot robots. A block diagram of the system integration of sensing and planning will illustrate the robot to robot interaction to operate as a collaborative unit. The proposed approach singular goal is to overcome the limits of previous approaches of robots in security applications and enabling systems to be deployed for autonomous operation in an unaltered environment providing access to an all encompassing sensor suite.

Our research has focused on how to expand the capabilities of an Omni-Directional Inspection Robot (ODIS) to assist in vehicle inspections at traffic control checkpoints with a standoff distance of 450m. We have implemented an mast, extendible to eight feet, capable of carrying a sensor payload that has an RS-232 connection with a simple set of commands to control its operation. We have integrated a communications chain that provides the desired distance and sufficient speed to transmit a live digital feed to the operator control unit (OCU). We have also created a physically-based simulation of ODIS and our mast inside of Webots and have taken data to calibrate a motion response model.

New laser accelerometer is presented. Proved method consists in the using of standing wave of coherent radiation in the linear resonator as the sensitive element of the accelerated movement measurement. There are not in new accelerometer named autonomous resonatory device (ARD) any matter parameters altering during movement of the resonator, attached with object to be measured. It provides the best accuracy in the measurements. Volume part of generalized function of eikonal for rectangle laser resonator is derived. Imaginary quantity of the eikonal provides the visible altering of amplitude of interacting field of baghron in space. Optical schemes of the prototypes are presented. ARD can be applied as measuring transducers for control of movement in demanded operating regions and it provides autonomous measurement of acceleration of actual motion at free falling of object as against to all other accelerometers.

Ordinary perimeter security systems consist of many individual sensors with detection range 200-300 meters. These limitations are connected with physical phenomena that are used in microwave and infrared barriers as well as in ground and fence cable sensors. On the contrary, fiber optic perimeter sensors can be applied in the range of many kilometers and zone length 200-300 meters is degradation of their possibilities. This paper presents investigation results of a new generation of the fiber optic perimeter sensor using WDM technique. These systems can detect a potential intruder and determine its position along a protected zone. The work presents a method of linear localization of disturbance point in the two-interferometer and modalmertic fiber optic sensors in one optical fiber. These sensors are in one fiber optic cable with two- interferometers (Sagnac) and in transmissive configuration. Using WDM technique makes it possible to obtain new technical properties that can broaden effectiveness and scope of application. Arrangement of a laboratory model of the sensors and its signal processing scheme is presented. During research of a laboratory model, it was possible to detect the position of the disturbance in one optical fiber with resolution of about 50m along a 10-km long sensor.

Classical theory of new autonomous laser accelerometer based on Galileo transformations, Maxwell equations and the complement condition is proposed. Presented description allows the using of standing wave of coherent radiation in the linear resonator as sensitive element of accelerated movement measurement. It appears that existence of field in form of baghron is necessary condition of invariance of Maxwell equations in irregular moving systems. It is shown that vector of radiation of infinite plane wave of light is equal to its wave vector. Generalized function of eikonal and Doppler-effect are observed. Laws of baghronica were discovered. Theory of laser accelerometer based on quantum operators was published with same results. Available future investigations are listed.

This paper proposes an innovative command and control system design and the use of low, cost distributed sensor networks for an intelligent maritime security system. This concept utilizes a network of small passive and active multi-phenomenological unattended sensors and shore based optical sensors to detect, classify, and track submerged threat objects approaching high value coastal assets, such as ports, harbors, residential, commercial, and military facilities and areas. The network of unattended, in-water sensors perform the initial detection, classification, and coarse tracking and then queues shore based optical laser radar sensors. These shore-based sensors perform a high resolution sector search to develop a precision track on the submerged threat objects. Potential threat objects include submarines, submerged barges, UUV's, swimmers carrying threat objects such as explosives, chemical, biological, radiological, and nuclear materials. Reliable systems with low false alarm rates (FAR) are proposed. Tens to hundreds of low cost passive sensors are proposed to be deployed conjunctively with several active acoustic and optical sensors in threat and facility dependant patterns to maximize the detection, tracking and classification of submerged threat objects.

Predicting failure in complex systems, such as satellite network systems, is a challenging problem. A satellite earth terminal contains many components, including high-powered amplifiers, signal converters, modems, routers, and generators, any of which may cause system failure. The ability to estimate accurately the probability of failure of any of these components, given the current state of the system, may help reduce the cost of operation. Probabilistic graphical models, in particular Bayesian networks, provide a consistent framework in which to address problems containing uncertainty and complexity. Building a Bayesian network for failure prediction in a complex system such as a satellite earth terminal requires a large quantity of data. Software monitoring systems have the potential to provide vast amounts of data related to the operating state of the satellite earth terminal. Measurable nodes of the Bayesian network correspond to states of measurable parameters in the system and unmeasurable nodes represent failure of various components. Nodes for environmental factors are also included. A description of Bayesian networks will be provided and a demonstration of inference on the Bayesian network, such as the calculation of the marginal probability of failure nodes given measurements and the maximum probability state of the system for failure diagnosis will be given. Using the data to learn local probabilities of the network will also be covered.

In the future, networks of unmanned and unattended sensor systems will replace many of these manned assets and will become pervasive and highly connected in many maritime areas. Unmanned mobile surveillance systems will be able to operate with a high degree of autonomy and weather tolerance with minimum cost and manpower risk. Low cost, highly sustainable underwater power sources, for both stationary sensors systems and mobile surveillance platforms, are required for this vision. This paper presents a description of interim results of investigations into technologies and systems for generating renewable energy from coastal and open ocean areas. A range of technologies have been investigated from low power systems deriving energy from the microbial fuel cells and the direct bacterial conversion of methane gas to methanol liquid to larger power systems deriving energy from ocean waves, methane hydrate deposits, and hydrothermal vents.

The US Army Corps of Engineers Research and Development Center participated in a joint ARL-NATO TG-53 field experiment and data collect at Yuma Proving Ground, AZ in early November 2005. Seismic and acoustic signatures from both muzzle blasts and impacts of small arms fire and artillery were recorded using 7 seismic arrays and 3 acoustic arrays. Arrays comprised of 12 seismic and 12 acoustic sensors each were located from 700 m to 18 km from gun positions. Preliminary analysis of signatures attributed to 60mm, 81mm, 120 mm mortars recorded at a seismic-acoustic array 1.1 km from gun position are presented. Seismic and acoustic array f-k analysis is performed to detect and characterize the source signature. Horizontal seismic data are analyzed to determine efficacy of a seismic discriminant for mortar and artillery sources. Rotation of North and East seismic components to radial and transverse components relative to the source-receiver path provide maximum surface wave amplitude on the transverse component. Angles of rotation agree well with f-k analysis of both seismic and acoustic signals. The spectral energy of the rotated transverse surface wave is observable on the all caliber of mortars at a distance of 1.1 km and is a reliable source discriminant for mortar sources at this distance. In a step towards automation, travel time stencils using local seismic and acoustic velocities are applied to seismic data for analysis and determination of source characteristics.

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis facilitate the development of a robust classification algorithm that reliably discriminates mortar and artillery variants via acoustic signals produced during the launch/impact events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants. Distinct characteristics arise within the different mortar variants because varying HE mortar payloads and related charges emphasize concussive and shrapnel effects upon impact employing varying magnitude explosions. The different mortar variants are characterized by variations in the resulting waveform of the event. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing techniques can employed to classify a given set. The DWT and other readily available signal processing techniques will be used to extract the predominant components of these characteristics from the acoustic signatures at ranges exceeding 2km. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients, frequency spectrum, and higher frequency details found within different levels of the multiresolution decomposition. The process that will be described herein extends current technologies, which emphasis multi modal sensor fusion suites to provide such situational awareness. A two fold problem of energy consumption and line of sight arise with the multi modal sensor suites. The process described within will exploit the acoustic properties of the event to provide variant classification as added situational awareness to the solider.

Integrating a sensor suite with ability to discriminate potential Chemical/Biological (CB) events from high-explosive (HE) events employing a standalone acoustic sensor with a Time Difference of Arrival (TDOA) algorithm we developed a cueing mechanism for more power intensive and range limited sensing techniques. Enabling the event detection algorithm to locate to a blast event using TDOA we then provide further information of the event as either Launch/Impact and if CB/HE. The added information is provided to a range limited chemical sensing system that exploits spectroscopy to determine the contents of the chemical event. The main innovation within this sensor suite is the system will provide this information on the move while the chemical sensor will have adequate time to determine the contents of the event from a safe stand-off distance. The CB/HE discrimination algorithm exploits acoustic sensors to provide early detection and identification of CB attacks. Distinct characteristics arise within the different airburst signatures because HE warheads emphasize concussive and shrapnel effects, while CB warheads are designed to disperse their contents over large areas, therefore employing a slower burning, less intense explosive to mix and spread their contents. Differences characterized by variations in the corresponding peak pressure and rise time of the blast, differences in the ratio of positive pressure amplitude to the negative amplitude, and variations in the overall duration of the resulting waveform. The discrete wavelet transform (DWT) is used to extract the predominant components of these characteristics from air burst signatures at ranges exceeding 3km. Highly reliable discrimination is achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients and higher frequency details found within different levels of the multiresolution decomposition. The development of an adaptive noise floor to provide early event detection assists in minimizing the false alarm rate and increasing the confidence whether the event is blast event or back ground noise. The integration of these algorithms with the TDOA algorithm provides a complex suite of algorithms that can give early warning detection and highly reliable look direction from a great stand-off distance for a moving vehicle to determine if a candidate blast event is CB and if CB what is the composition of the resulting cloud.

Traditional correlation filtering methods produce classification results by processing one image frame at a time. The filters are designed to yield well defined correlation peaks when a pattern or object of interest is present in the input image. However, the decision process is memory-less, and does not take advantage of the history of results on previous frames in a sequence. Recently, Kerekes and Kumar introduced a new Bayesian approach for multi-frame correlation that first produces an estimate of the object's location based on previous results, and then builds up the hypothesis using both the current data as well as the historical estimate. In this paper, we examine a simple approximation to their approach which directly uses the correlation filter outputs while avoiding the need for density functions and explicit probability calculations. Preliminary analysis shows that the simplified approach has the potential for also yielding significant performance improvements over the conventional approach based on individual frames.

A simple model is presented of a possible inspection regimen applied to each leg of a cargo containers' journey between its point of origin and destination. Several candidate modalities are proposed to be used at multiple remote locations to act as a pre-screen inspection as the target approaches a perimeter and as the primary inspection modality at the portal. Information from multiple data sets are fused to optimize the costs and performance of a network of such inspection systems. A series of image processing algorithms are presented that automatically process X-ray images of containerized cargo. The goal of this processing is to locate the container in a real time stream of traffic traversing a portal without impeding the flow of commerce. Such processing may facilitate the inclusion of unmanned/unattended inspection systems in such a network. Several samples of the processing applied to data collected from deployed systems are included. Simulated data from a notional cargo inspection system with multiple sensor modalities and advanced data fusion algorithms are also included to show the potential increased detection and throughput performance of such a configuration.

Area Protection Network (APN) is a concept for autonomous surveillance and perimeter protection. It is a network of sensors, software and a command & control system. The purpose is to protect military and civilian objects and installations with an all-weather, 24-hour, modular, low-cost and mobile system. The system shall primarily be able to detect and track human activity in the area of interest and also detect and classify behaviour in order to trig appropriate actions. In order to show the concept in real life, an operational demonstrator was developed during 2006. The APN demonstrator currently consists of a radar (SIRS77), infrared sensors (PTES), visual sensors (video camera), image processing and data fusion software (Impress) and a command and control system (WCU) The APN demonstrator can currently detect and track multiple humans and/or vehicles in limited 3D. The tracks are presented on a map in the operator's graphical user interface. The operator can define multiple alarm zones in the map. If any track enters an alarm zone an alarm is triggered. The system also includes "blue force" tracking.

This paper presents a new technique for automatic detection of marine vehicles in open sea from a buoy camera system using computer vision approach. Users of such system include border guards, military, port safety and flow management, sanctuary protection personnel. The system is intended to work autonomously, taking images of the surrounding ocean surface and analyzing them on the subject of presence of marine vehicles. The goal of the system is to detect an approximate window around the ship and prepare the small image for transmission and human evaluation. The proposed computer vision-based algorithm combines horizon detection method with edge detection and post-processing. The dataset of 100 images is used to evaluate the performance of proposed technique. We discuss promising results of ship detection and suggest necessary improvements for achieving better performance.

Maritime borders and coastal zones are susceptible to threats such as drug trafficking, piracy, undermining economical activities. At TNO Defence, Security and Safety various studies aim at improving situational awareness in a coastal zone. In this study we focus on multi-sensor surveillance of the coastal environment. We present a study on improving classification results for small sea surface targets using an advanced sensor suite and a scenario in which a small boat is approaching the coast. A next generation sensor suite mounted on a tower has been defined consisting of a maritime surveillance and tracking radar system, capable of producing range profiles and ISAR imagery of ships, an advanced infrared camera and a laser range profiler. For this suite we have developed a multi-sensor classification procedure, which is used to evaluate the capabilities for recognizing and identifying non-cooperative ships in coastal waters. We have found that the different sensors give complementary information. Each sensor has its own specific distance range in which it contributes most. A multi-sensor approach reduces the number of misclassifications and reliable classification results are obtained earlier compared to a single sensor approach.

New trends in development of optoelectronic and radar systems with mixed technologies for detection, identification and visualization for critical infrastructure protection are presented. Network-based communication as well as new algorithms of intelligent vision surveillance and image fusion is described.

In the wake of an increasing number of terrorist attacks, counter-terrorism measures are now a main focus of many research programmes. An important issue for the police is the ability to track individuals and groups reliably through underground stations, and in the case of post-event analysis, to be able to ascertain whether specific individuals have been at the station previously. While there exist many motion detection and tracking algorithms, the reliable deployment of them in a large network is still ongoing research. Specifically, to track individuals through multiple views, on multiple levels and between levels, consistent detection and labelling of individuals is crucial. In view of these issues, we have developed a change detection algorithm to work reliably in the presence of periodic movements, e.g. escalators and scrolling advertisements, as well as a content-based retrieval technique for identification. The change detection technique automatically extracts periodically varying elements in the scene using Fourier analysis, and constructs a Markov model for the process. Training is performed online, and no manual intervention is required, making this system suitable for deployment in large networks. Experiments on real data shows significant improvement over existing techniques. The content-based retrieval technique uses MPEG-7 descriptors to identify individuals. Given the environment under which the system operates, i.e. at relatively low resolution, this approach is suitable for short timescales. For longer timescales, other forms of identification such as gait, or if the resolution allows, face recognition, will be required.

Presented here is a novel clustering method for Hidden Markov Models (HMMs) and its application in acoustic scene analysis. In this method, HMMs are clustered based on a similarity measure for stochastic models defined as the generalized probability product kernel (GPPK), which can be efficiently evaluated according to a fast algorithm introduced by Chen and Man (2005) [1]. Acoustic signals from various sources are partitioned into small frames. Frequency features are extracted from each of the frames to form observation vectors. These frames are further grouped into segments, and an HMM is trained from each of such segments. An unknown segment is categorized with a known event if its HMM has the closest similarity with the HMM from the corresponding labeled segment. Experiments are conducted on an underwater acoustic dataset from Steven Maritime Security Laboratory, Data set contains a swimmer signature, a noise signature from the Hudson River, and a test sequence with a swimmer in the Hudson River. Experimental results show that the proposed method can successfully associate the test sequence with the swimmer signature at very high confidence, despite their different time behaviors.

This paper describes an innovative miniature optical sensor for measuring the turbulence in water columns. The turbulence sensor consists of a single-frequency laser transmitter and a photodetector on which the scattered light from the turbulent water is coherently mixed with a sample of the transmitted beam. This miniature sensor could be used on mobile platforms, such as unmanned underwater vehicles (UUV's), to wake follow platforms, schools of fish or marine mammals or on stationary unattended underwater sensors to monitor natural turbulence in littoral waters. Arrays of fixed unattended sensors could be used to detect the wake of transiting submerged vehicles, scuba divers, marine mammals or large schools of fish. A mobile platform equipped with a miniature turbulence sensor could to be cued to the general location and depth of an underwater target and then the platform could use this small aperture sensor to acquire and follow the wake. This turbulence sensor system could be miniaturized and packaged into a very small volume; approximately the size of a wristwatch.

Unattended Ground Sensors (UGS) were first used to monitor Viet Cong activity along the Ho Chi Minh Trail in the 1960's. In the 1980's, significant improvement in the capabilities of UGS became possible with the development of digital signal processors; this led to their use as fire control devices for smart munitions (for example: the Wide Area Mine) and later to monitor the movements of mobile missile launchers. In these applications, the targets of interest were large military vehicles with strong acoustic, seismic and magnetic signatures. Currently, the requirements imposed by new terrorist threats and illegal border crossings have changed the emphasis to the monitoring of light vehicles and foot traffic. These new requirements have changed the way UGS are used. To improve performance against targets with lower emissions, sensors are used in multi-modal arrangements. Non-imaging sensors (acoustic, seismic, magnetic and passive infrared) are now being used principally as activity sensors to cue imagers and remote cameras. The availability of better imaging technology has made imagers the preferred source of "actionable intelligence". Infrared cameras are now based on un-cooled detector-arrays that have made their application in UGS possible in terms of their cost and power consumption. Visible light imagers are also more sensitive extending their utility well beyond twilight. The imagers are equipped with sophisticated image processing capabilities (image enhancement, moving target detection and tracking, image compression). Various commercial satellite services now provide relatively inexpensive long-range communications and the Internet provides fast worldwide access to the data.

Persistent aerial video surveillance from small UAV (SUAV) platforms requires accurate and robust target tracking capabilities. However, video tracks can break due to excessive camera motion, target resolution, low signal-to noise ratio, video frame dropout, and frame-to-frame registration errors. Connecting broken tracks (video track repair) is thus essential for maintaining high quality target tracks. In this paper we present an approach to track repair based on multi-hypothesis sequential probability ratio tests (MHSPRT) that is suitable for real-time video tracking applications. To reduce computational complexity, the approach uses a target dynamics model whose state estimation covariance matrix has an analytic eigendecomposition. Chi-square gating is used to form feasible track-to-track associations, and a set of local hypothesis tests is defined for associating new tracks with coasted tracks. Evidence is accumulated across video frames by propagating posterior probabilities associated with each track repair hypothesis in the MHSPRT framework. Global maximum likelihood and maximum a posteriori estimation techniques resolve conflicts between local track association hypotheses. The approach also supports fusion of appearance-based features to augment statistical distributions of the track state and enhance performance during periods of kinematic ambiguity. First, an overview of the video tracker technology is presented. Next the track repair algorithm is described. Finally, numerical results are reported demonstrating performance on real video data acquired from an SUAV.

The depth of field of optical systems can be extended with a phase mask placed in the pupil. We propose to design this phase mask through a heuristic numerical optimization. We describe two different criteria to illustrate the technique. We present the obtained phase profiles and we show that they have good properties regarding the extension of the depth of field.

Digital holography in the mid infrared range is shown to be a feasible technique for optical metrological applications. The technique allows to reconstruct both amplitude and phase of wavefronts scattered by a 3D object. Experimental results of the method applied to the reconstruction of digitally holograms recorded at CO₂ laser wavelength of 10.6 micron are reported. It is show that good reconstructions can be obtained even with the lower spatial resolution of IR recording detectors compared to visible CCD array. The results show that new prospective can be exploited by using high power CO₂ laser sources in optical metrological applications.

Integral imaging systems permit to capture and reproduce three-dimensional scenes. However they usually suffer from a limited depth of field and/or limited depth of focus that severely reduces the depth range that can be used in practice. In order for such a system to be able to capture and reproduce large-depth scenes without any adjustment, we propose to include in the integral imaging system an array of phase masks in order to increase the depth of focus of the final three-dimensional images. We consider both the pickup and the reconstruction stages.

Flash LADAR systems are becoming increasingly popular for robotics applications. However, they generally provide a low-resolution range image because of the limited number of pixels available on the focal plane array. In this paper, the application of image super-resolution algorithms to improve the resolution of range data is examined. Super-resolution algorithms are compared for their use on range data and the frequency-domain method is selected. Four low-resolution range images which are slightly shifted and rotated from the reference image are registered using Fourier transform properties and the super-resolution image is built using non-uniform interpolation. Image super-resolution algorithms are typically rated subjectively based on the perceived visual quality of their results. In this work, quantitative methods for evaluating the performance of these algorithms on range data are developed. Edge detection in the range data is used as a benchmark of the data improvement provided by super-resolution. The results show that super-resolution of range data provides the same advantage as image super-resolution, namely increased image fidelity.

Networks of sensors are an emerging technology for real-time data gathering in a wide variety of civilian and military applications. Sensor networks comprise a large number of miniature nodes with sensing, computing and wireless communication capabilities and are randomly deployed in an area or volume of interest that may be remote or hazardous especially in defense applications. Using optical wireless communication (OWC) a population of sensor nodes can be located and mapped and encoded data can be transmitted to the base station. In this paper we review some theoretical and experimental work in this area and underline some of the challenges and possible solutions.

The mass and the power consumption are the most constrictive restrictions in an Aerostatic Platform. We present in this work a bidirectional link based on a liquid crystal retro-modulator (LCRM). The use of this device displaces to the terrestrial station the tasks of powering the laser, and the pointing mechanism. Also, due to the non-conductive characteristic of the LCRM, the power requirements are low. The beam aperture of the upward link can be tailored with the compromise between the aperture losses, and the tracking mechanics. The range of the distances for the system presented is from 2 to 20 km, being the lower limit for the tests and checking of the system, and the higher the final system for a stratospheric survey Aerostat. The system will be modified to fulfill the requirements associated to the increasing distances, although the main characteristics (modulation schemes, modulator, etc.) will be maintained. The system uses two modulation schemes for each direction: in the uplink a carrier constant envelope FSK modulation is used. For the down link, part of the optical signal is polarization modulated and reflected to the earth. For increasing the data rate, a multi-polarization modulation is used. Actually, 32 polarization levels are used, increasing the data rate in a 5-fold factor. The use of differential scheme, i.e. the State of Polarization (SOP) change defines the data, not the SOP, avoids the necessity of SOP maintenance in the transmitter.

It seems like just yesterday that 10 Gb/s (OC-192) transmission was the norm in data rates with slower data rates disappearing! The particular bit-rate jump to 40 Gb/s (OC-768) is not a trivial task. Electronic designers now face serious complexities as they push the technology to the limit. Issues such as chromatic dispersion and polarization mode dispersion are placing more stringent requirements on fiber optics and associated components. The requirement to gather and transfer data at faster and faster rates has spurned an evolution in the thought processes of Photonic engineers. It appears that to handle the ever-increasing bandwidths, Photonic techniques are the way to go! Sophisticated analog-to-digital converters and polymer-based modulator systems are now being designed and tested in Air Force government laboratories. Only time will tell if these designs can handle the voluminous amounts of data!

Compared to traditional microwave systems for intersatellite communication, optical intersatellite links offer numerous advantages for example lower weight and power consumption as well as higher bit rates. In addition, the smaller diameter of the laser beam allows a higher data security. The coherent optical terminal developed by TESAT Spacecom offers a bandwidth of 5.5 Gbps with a range of 10,000 km and a bit error ratio below 1e-9. In 2007, the coherent optical terminal will be verified in orbit. The transmitter consists of a ring oscillator and an optical amplifier. For both components, a high reliable diode laser pump module is essential to meet the demanded lifetime requirements of 10 years with a reliability of 0.9998. Built-in cold and hot redundancy as well as a truly hermetically sealed housing increase the reliability of the pump module. To prove its suitability for space applications, the module has been successfully qualified in terms of radiation, vibration, mechanical shock and thermal cycling. The laser radiation of two diode laser bars consisting of six emitters is coupled in a 100 µm NA=0.22 fiber. The coupling efficiency as well as the mounting accuracy of the optical components have been analyzed by raytracing. To predict the effect of different heat sink materials and to calculate the temperature drop over the module, a 3D finite element analysis has been performed. The rated optical output power of the module described in this paper amounts to 10 W, and it measures 50 mm x 50 mm x 20 mm.

An optical communication link with a modulated retro-reflector in a cat's eye optics arrangement has been evaluated. A transmissive multiple quantum well modulator with a modulation bandwidth in excess of 10 MHz was placed in a wide field-of-view cat's eye optic system. A laser transceiver with one line and one broadband source around 1550 nm was used to interrogate the modulated retro-reflector and detect the reflected and modulated signal. Multi-level digital encoding was evaluated as a way to increase the information transfer rate in conditions with relatively high signal-to-noise ratio. The links were evaluated in indoor as well as outdoor conditions.

Free-space optical communications have distinct advantages over conventional RF and microwave systems by virtue of their high carrier frequencies that permit high modulation bandwidth, enhanced security, freedom from interference, and low power. However, the turbulent atmosphere causes phase variations along the path that are manifested in intensity variations (scintillation) and beam profile distortion and boresight wander. These variations manifest as a multiplicative noise source that reduces the ability of the receiver to determine the information contained in the modulation. For many years, the emphasis throughout this area has been on elucidating those implications of the atmospheric propagation problem that bear on the design and performance of optical communication systems. In this work, it is our intention to elucidate how the addition of adaptive optics to the transmitter or receiver can reduce the effects of atmospheric propagation and, in so doing, to quantify the improvement on the performance of optical communications systems regarding coherent detection.

In wireless optical communications, information is carried by coherent laser beams propagating through the free space. In realized communication channels, the standard beams created directly in the laser resonator are utilized. In recent time, an increasing attention has been focused on the so-called nondiffracting beams generated by auxiliary optical systems. In this paper, the theoretical and experimental aspects of the nondiffracting propagation of light are discussed and geometrical parameters and physical properties of nondiffracting beams promising for wireless communications reviewed.