We argue that visual conspicuity and identifiability are two efficient task-related measures that can be deployed to calibrate synthetic imagery that is intended to be used for human visual search and detection tasks. The conspicuity of a target is operationally defined as the region around the center of the visual field where the target is capable to attract visual attention. Visual conspicuity predicts human visual search performance in realistic and military relevant complex scenario's. Conspicuity can easily and quickly be measured either in the field (in complex environments) or in the lab. This eliminates the need for costly and time consuming visual search experiments. The agreement between field and lab measurements implies that conspicuity can be used to validate synthetic imagery. Target identifiability is operationally defined as the amount of Gaussian blur that is required to reduce the target signature to its identification threshold. It is an efficient metric that can be used to gain insight into human identification performance without having to resort to elaborate and costly experiments. Identifiability is directly related to PID-performance, and is therefore well suited for comparing synthetic and realistic imagery. We conclude that synthetic imagery can be calibrated for human visual search and detection tasks by setting the conspicuity and identifiability of targets equal to those of their real world counterparts.

A segment of the modeling and simulation community and key decision makers still hold to the misconception that a vehicle can have a single or a representative thermal "signature" for a given scenario-such as daytime summer or night time summer. In truth, a vehicle in a "daytime summer Northeast Asia" scenario can manifest many different types of detectabilities and signature manifestations throughout the day and under differing weather conditions. A reasonable approach toward representing a vehicle's signature characteristics would be to understand that data spread and choose the best value or values that address the question asked of a particular simulation. The Army Materiel Systems Analysis Activity (AMSAA) is moving towards addressing this problem and is seeking to use modeling and Simulation (M&S) tools to populate its databases in a reasonable manner. Using the latest M&S tools, the authors will present unclassified results of measurements and simulations demonstrating this data spread and the resulting CASTFOREM sensitivity analysis. Images and the Delta T-RSS metric will be used to demonstrate the concept of the data distribution. By moving toward the signature data spread mentality, the research and development community can help the sensor and operations community pick the appropriate values for particular analyses--even for vehicles that are in the concept design phase.

Optical detection systems usually rely on the intensity contrast (visible) or temperature difference (infrared) between target and background. Adding new dimensionality to the detection process is essential to enhance the sensitivity. This paper presents a novel theory for modeling the performance of an optical detection technique called Interferogram Phase Step Shift (IPSS), which relies on the coherence contrast between target and background to perform discrimination. The technique uses an interferometer to measure the self-coherence function of the input radiation, forming an interferogram, and an interference filter to produce an event marker (phase step) in it. The model predicts the displacement of the phase step in the interferogram, when a coherent target enters the system field of view, which is the kernel of the IPSS technique. The paper assesses the effects of the target to optical filter bandwidth ratio in the system responsivity, for optimization purposes, and models the experiments presented in a previous publication, predicting the experimental results theoretically to perform a comparison. It also includes the analytical derivation of the self-coherence functions of target and background as measured by the system's interferometer, and the computer modeling of the same self-coherence functions for an interference filter, with any arbitrary spectral response, considering the effects of the polarization of the light sources and optical components in the experiments. Finally, the theoretical curves for displacement vs. target-to-background power ratio, among others, are compared with the experimental results. Good agreement is demonstrated, and the causes of differences are discussed.

Visual target discrimination has occurred when the observer can say "I see a target THERE!" and can designate the target location. Target discrimination occurs when a perceived shape is sufficiently similar one or more of the instances the observer has been trained on. Marr defined vision as "knowing what is where by seeing." Knowing "what" requires prior knowledge. Target discrimination requires model-based visual processing. Model-based signature metrics attempt to answer the question "to what extent does the target in the image resemble a training image?" Model-based signature metrics attempt to represent the effects of high-level top-down visual cognition, in addition to low-level bottom-up effects. Recent advances in realistic 3D target rendering and computer-vision object recognition have made model-based signature metrics more practical. The human visual system almost certainly does NOT use the same processing algorithms as computer vision object recognition, but some processing elements and the overall effects are similar. It remains to be determined whether model-based metrics explain the variance in human performance. The purpose of this paper is to explain and illustrate the model-based approach to signature metrics.

The SR 5000 Infrared spectroradiometer, developed in the mid '80's, is a robust research tool for the electro-optics system development laboratory. It has been the top-of-the-line IR spectroradiometer since then, with high sensitivity and useful software packages for data analysis, but its user interface became outdated, because of the enormous advances that personal computers underwent in the 90's. Recently, after being on the verge of disappearance, CVF based spectroradiometry has been revived. Here we present some important new features of the system: 1. Synchronized imaging. A CCD camera is boresighted with the line of sight of the SR 5000, to digitally record the image of the measured object and its background, in synchronization with the spectral measurement. This feature is useful in the field to avoid mishaps, and sometimes for later analysis of the results. 2. Windows Operating System. The new system control, storage and analysis software package has been developed to take advantage of modern PC's, generally accepted user interface modalities, and a powerful database for file management.

Recently, new image processing techniques have been researched for application in many areas, such as biomedical, telecommunications, multimedia, remote sensing and optics. Multigrid and multirate processing of two-dimensional (2D) signals can be used in order to get a basis and consistent theory. Since it involves many types of lattices due to different grids geometry, they can be used as support of a consistent multirate processing theory for image applications. In this work, the concepts of lattice theory are used to make the rectangular, quincunx and hexagonal grid types modeling. The multirate processing of 2D signals involves also downsampling and upsampling and various types of sampling matrices and their formation are analyzed and grid types determined by them are shown.

The exhaust gas plume is an important and sometimes dominating contributor to the infrared signature of ships. Suppression of the infrared ship signatures has been studied by TNO for the Royal Netherlands Navy over considerable time. This study deals with the suppression effects, which can be achieved using a spray of cold water in the inner parts of the exhaust system. The effects are compared with the effect of cooling with air. A typical frigate size diesel engine serves as an example for gas flow, composition and temperature of the plume. The infrared emission of the cooled an un-cooled exhaust gases is calculated. Both the spectral behaviour and the integrated values over typical bands are discussed. Apart from the signature also some advantages of water exhaust gas cooling for the ship design are discussed.

This research investigates the classification of battlespace detonations, specifically the determination of munitions type and size using image features from an infrared wavelength camera. Experimental data are collected for the detonation of several types of conventional munitions with different high explosive materials and different weights. Key features are identified for discriminating various types and sizes of detonation flashes. These features include statistical parameters derived from the time dependence of fireball size. Using Fisher linear discriminant techniques, these features are projected onto a line such that the projected points are maximally clustered for different classes of detonations. Bayesian decision boundaries for classification are then determined.

Vehicles concealed in highly cluttered, vegetated scene environments pose significant challenges for passive sensor systems and algorithms. System analysts working hyperspectral exploitation research require an at-aperture simulation capability that allows them to reliably investigate beyond the highly-limited scenarios that expensive field data sets afford. To be useful to the analyst, such a simulation should address the following requirements: (1) the ability to easily generate scene representations for arbitrary Earth regions of tactical interest; (2) the ability to represent scene components, like terrain, trees and bushes, to an extremely high spatial resolution for calculation of accurate multiple spectral reflections, occlusions and shadowing; (3) the ability to stimulate the 3D scene with realistic natural spectral irradiances for arbitrary 3D model atmospheres; (4) the ability to appropriately integrate constantly improving, rigorous thermal, spectral signature and atmospheric propagation models; (5) the ability to efficiently render at-aperture hyperspectral data sets in a reasonable run-time. Herein the authors describe their work toward a comprehensive ray-tracer-based simulation architecture and prototype capability that addresses these requirements. They describe their development of a GIS-based toolset for database generation, tools for 3D vegetated terrain-model development, and a prototype raytracer-based spectral scene generator.

UWB communication is essentially the transmission and receiving of ultra short electromagnetic energy pulses. Short pulses mean wide bandwidths, often greatly exceeding 25% of the nominal center frequency. Modern UWB radio is characterized by very low power transmission (in the range of tens of microwatts) and wide bandwidths (greater than a gigahertz). One of the major applications of Ultra-wide band technology has been for detection and tracking of intruders in different environments. Based on some of our previous work [1,2] we developed a hybrid Ray-tracing/FDTD technique to study the indoor and outdoor propagation of UWB signals. The basic goal of this paper is to describe the experimental and simulation studies that were conducted to locate and track an intruder inside a UWB sensor web system. The sensor was developed using the Time Domain P-200 device and the software was developed using MATLAB. Return scans from UWB devices are analyzed to determine the noise floor and the signal strength. Using the noise floor level a threshold level is set above which the alarm will be triggered to determine the presence of an intruder. The probability of false alarm (PFA) is also determined using the Signal-to-Noise ratio and the threshold. We vary the PFA to lower the false alarm to a minimum level. We also determine the noise statistics of the system using Non-parametric Kolmogorov-Smirnov (KS) test. Using this basic UWB sensor web system we will try to determine the physical dimensions of the intruder and also track multiple intruders on the system.

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

The simulation workshop CHORALE of the French DGA is used by government services and industrial companies for weapon system validation and qualification trials in the infrared domain, and detection of moving vehicles in the acoustic domain. Recently, acoustic simulation tests were performed on the 3D geometrical database of the DGA/DCE/ETBS proving ground. Results have been compared to the acoustic measurements of the NATO-TG25 trials. This article describes the trials, the modeling of the 3D geometrical database and the comparison between acoustic simulation results and measurements. The 3D scene is described by a set of polygons. Each polygon is characterized by its acoustic resistivity or its complex impedance. Sound sources are associated with moving vehicles and are characterized by their spectra and directivities. A microphone sensor is defined by its position, its frequency band and its directivity. For each trial, atmospheric profiles (air temperature, pressure and humidity according to altitude), trajectories and sound spectrum of moving objects were measured. These data were used to prepare the scenario for the acoustic simulation.

ADRPM (Acoustic Detection Range Prediction Model) is a software program that models the propagation of acoustic energy through the atmosphere and evaluates detectability. ADRPM predicts the distance of detection for a noise source based on the acoustic signature of the source. In this paper the assessment of the acoustic signature which characterizes a vehicle is performed by the conventional Boundary Element Analysis (BEA), and by the Energy Boundary Element Analysis (EBEA). BEA is used for computing the radiated noise for the 1/3 octave bands up to 500Hz, and the EBEA is used for the remaining frequency range. By combining the conventional BEA (for low frequency) with the EBEA (for high frequency), it is possible to perform noise radiation computations over the entire frequency range in a seamless manner. Once the initial detection range is predicted, the main contributors to the acoustic detection are identified and their location on the vehicle is modified in order to assess the corresponding effect to the detectability.

Advanced sensor systems prototypes using active illumination systems hold the promise of both range and background discrimination detection capabilities. However, the impact of optical turbulence on such systems is not minimal. Since these systems operate in the near-visible SWIR band, the influences of both image distortion and illumination pulse scintillation will affect system performance. Understanding the nature of these turbulent impacts can aid in setting system parameters that minimize turbulence degradation while maximizing system performance. In this paper we highlight simulation techniques for modeling image distortion due to a combination of limited isoplanatic patch size and angle of arrival variations due primarily to large scale turbulent eddies. In addition, we discuss the simulation of the laser pulse illumination via phase screen propagation. We then illustrate these effects via simulation of target images.

Increasingly, the signature management community is demanding modeling tools for a variety of purposes from real-time simulations to complex modeling tasks. RenderView is one of the tools which has been developed and continues to evolve in response to this demand. The focus of RenderView development has been physics based modeling of high complexity both geometrically and with respect to surface optical properties. RenderView incorporates full bi-directional reflectance distribution function (BRDF) models and measured and calibrated global illumination maps. With these tools comes the capability to evaluate with a very high level of fidelity the impact of vehicle geometric and surface properties on its visible and thermal signature. A description of RenderView will be presented in terms of its focus on high fidelity models of vehicles and materials. A number of examples will be presented that show how the fidelity of the BRDF impacts the signature via the rendering model.

The advancement of computer simulation tools for high fidelity signature modeling has led to a requirement for a better understanding of effects of light scattering from surfaces. Measurements of the Bidirectional Reflectance Distribution Function (BRDF) fully describe the angular scattering properties of materials, and these may be used in signature simulations to quantitatively characterize the optical effects of surface treatments on targets. This paper reviews the theoretical and experimental techniques for characterizing the BRDF of surfaces and examines some of the popular parameterized BRDF representations that are used in signature calculations.

At least in the visible and near infrared spectral region the basic principles about the bi-directional reflectance distribution function (BRDF) have achieved an advanced state. This basic knowledge has been summarized by international well known scientists and firstly published in a book. A CD-ROM data base is attached to the book. For this paper these data have been used for a very first statistical synopsis. The measurement results of different scientists for similar targets and similar geometric conditions differ partly to a great extent. Hence mean values and variances cannot presently be used to describe the BRDF of different surfaces. The anisotropy factor defined by Sandmeier seems appropriate to be used in some investigations. The data sets are not sufficient for serious statistical analyses. Further measurements are essential to overcome the gap from examples to confidential statistical evaluations. In the last section the measurement methods planned by the University of Stuttgart for a ground measuring device and by target pointing of a small satellite are discussed.

The Bi-directional Reflectance Distribution Function (BRDF) is a general way to represent reflection from surfaces. However, even when ignoring variations in location and wavelength, the BRDF is still a 4-dimensional function and the number of BRDF samples necessary for direct utilization can impose severe computational requirements. To address these and other problems, analytical BRDF equations have been developed for computer image simulations. Limitations remain since they may be empirical, appropriate only for specific surfaces, or require difficult-to-obtain physical parameters. BRDF shading based on signal processing methods has recently been presented in computer graphics that projects any BRDF onto an orthogonal basis set and then employs a truncated linear series for shading with controlled accuracy. This paper presents an overview of BRDF shading and frequency-space representations using orthogonal polynomials as basis functions. Techniques are then described that utilize the resulting linear shading equations to factor lighting and geometry components of a scene for image-based re-lighting. Statistical properties of images may then be partially computed for fixed views in a pre-process phase and employed to rapidly compute view properties for arbitrary lighting distributions and different BRDFs. Techniques are also described for producing correct blended BRDFS aimed at level-of-detail frequency-space shading.

The bidirectional reflectance distribution function (BRDF) for a surface is an important quantity in simulation and prediction of ultraviolet, visible and infrared signatures from objects. In this paper we briefly give some background for modelling of rough surface scattering and present a selection of models for scattering of light from rough surfaces. Emphasis is placed on some analytical (approximate), physics-based methods, through which the BRDF can be calculated from surface topography and material optical data. Ranges of validity and limitations of the models are discussed. We also touch upon the relation between these analytical models and some more empirical, parametric, models for BRDF which are sometimes used in computer programs for three-dimensional visualization and scene simulation. Some examples from calculations using rough surface scattering models are presented.

We present a new portable infrared-based hemispherical scatterometer to rapidly and accurately determine out of plane reflectance function (BRDF) of homogeneous surfaces. The position of the 12 detectors has been selected based on angular distribution scheme of the S4 quadrature of the discrete-ordinates method. The reflectance data obtained from this device can be directly applied to radiation transport schemes for problems involving highly accurate surface characterization. With this instrument infrared energy scattering can be performed in multiple directions and sequences at the same time. With measurements for a variety of fire barrier materials used in non-bearing walls we demonstrated the usefulness of this apparatus over a limited range of scattering directions. Verification of the measurements is done by comparing theoretical and experimental data of radiative intensity distribution in fire blanket insulation when impinged by a collimated flux and using an opaque reflector with arbitrary properties but previously determined reflectance function as a radiative boundary. The same equipment can be used to measure other radiative properties for different materials and it has been envisioned as a portable tool for rapid property and surface defects estimation in manufacturing processes.

Contact surface temperature measurement in the field is essential in trials of thermal imaging systems and camouflage, as well as for scene modeling studies. The accuracy of such measurements is challenged by environmental factors such as sun and wind, which induce temperature gradients around a surface sensor and lead to incorrect temperature readings. In this work, a simple method is used to test temperature sensors under conditions representative of a surface whose temperature is determined by heat exchange with the environment. The tested sensors are different types of thermocouples and platinum thermistors typically used in field trials, as well as digital temperature sensors. The results illustrate that the actual measurement errors can be much larger than the specified accuracy of the sensors. The measurement error typically scales with the difference between surface temperature and ambient air temperature. Unless proper care is taken, systematic errors can easily reach 10% of this temperature difference, which is often unacceptable. Reasonably accurate readings are obtained using a miniature platinum thermistor. Thermocouples can perform well on bare metal surfaces if the connection to the surface is highly conductive. It is pointed out that digital temperature sensors have many advantages for field trials use.

In this paper, we present our first results towards understanding high temporal frequency thermal infrared response from a dense grass canopy. The model is driven by slowly varying, time-averaged meteorological conditions and by high frequency measurements of local and within canopy profiles of relative humidity and wind speed, and compared to high frequency thermal infrared observations. Previously, we have employed three-dimensional ray tracing to compute the intercepted and scattered solar and IR radiation fluxes and for final scene rendering. For the turbulent fluxes, simple resistance models for latent and sensible heat with one-dimensional profiles of relative humidity and wind speed are used. Our modeling approach has proven successful in capturing the directional and diurnal variation in background thermal infrared signatures. We hypothesize that at these scales, where the model is typically driven by time-averaged, local meteorological conditions, the primary source of thermal variance arises from the spatial distribution of sunlit and shaded foliage elements within the canopy and the associated radiative interactions. In recent experiments, we have begun to focus on the high temporal frequency response of plant canopies in the thermal infrared at 1 sec to 5 min intervals. At these scales, we hypothesize turbulent mixing plays a more dominant role. Our results indicate that in the high frequency domain, the vertical profile of temperature change is tightly coupled to the within canopy wind speed. In the results reported here, the canopy cools from the top down with increased wind velocities and heats from the bottom up at low wind velocities.

Modeling of material reflectance in simulated infrared/electro-optical scenes is typically done assuming a Gaussian distribution or similar simple statistical model, because of limited available measured data. Such an approach fails to capture the true reflectance statistics for active systems such as laser sensors. A new approach developed for a data-rich environment will be described, as applied to a laser sensor simulation. This approach utilizes a large database of recently collected laser sensor data to derive reflectance histograms for each material type in a scene. Simulated imagery using such sampled histograms is much more faithful to actual system imagery than that based on traditional statistical models. The paper will describe the material database and the algorithms by which it is utilized in the simulation, and will present resulting simulated imagery and comparisons to simulated imagery using Gaussian reflectivity models.

Simple statistical models for clutter are desirable for parametric modelling of sensors and the development of constant false alarm rate detection processing. In the case of radar sensors and sea clutter there are a few widely known and accepted 'standard' models that can be employed. For passive infra-red sensors there are fewer models and no such widely accepted model applicable to sea clutter. In this paper a statistical model for the behaviour of sea clutter in the long-wave infra-red is presented. The model is based upon many of the same assumptions that lead, in the case of radar, to the well-known and widely used K-distribution model. It is compared with real long-wave infra-red sea clutter data gathered in trials from a variety of locations.

Advanced techniques for generating infrared (IR) scenes of a maritime environment for use in an imaging infrared (IIR) Anti-Ship Cruise Missile (ASCM) are discussed. The enhancements include the incorporation of a cluttered sea surface using an improved version of the Mermelstein sea-surface model. The US Naval Research Laboratory has implemented this capability for generating uncorrelated clutter into IR scenes for use in the CRUISE_Missiles ASCM model. These techniques for capturing the more complex features of the environment will become increasingly important as more low-observable (LO) ships, advanced imaging ASCMs and new IR decoy techniques are designed and deployed. This paper presents the design and implementation of a static clutter model, as well as a qualitative validation of the synthesized scenes based on field data.

CAMEO-SIM is a unique, broadband, EO synthetic scene generation system that has been developed by INSYS Ltd. (formerly Hunting Engineering) in conjunction with the Air Systems Department of Dstl Farnborough, in the UK. The aim of the software is to provide synthetic imagery for all battlefield electro-optic sensors. CAMEO-SIM models real word physics to render high fidelity, 3-D synthetic scene imagery. The code is the tool of choice for the UK MOD and has a growing customer base in Europe and in the U.S. CAMEO-SIM was originally conceived to asses the effectiveness of air vehicle camouflage schemes. The application has since been extended to model ground-based scenarios and more recently an ocean models has been developed, to serve the Naval community. This paper presents an overview of the ocean model development, a description of the techniques and algorithms that have been employed in modeling the sea surface and a summary of the model has been developed, to serve the naval community. This paper presents an overview of the ocean model development, a description of the techniques and algorithms that have been employed in modeling the sea surface and a summary of the model validation work that has been undertaken to date.

This paper describes the high temporal (1 sec to 5 min) and spatial thermal infrared directional characterization of low dense grass canopy during high humidity conditions to study the diurnal and spatial variation of simple vegetation background signatures. The instruments used in the characterization effort consisted of two infrared cameras (8-14 μm) set at nadir and 45 degrees, four sets of radiometers (3-5 μm and 8-12 μm), micrometeorological instruments, and thermocouples placed within the grass. Micrometeorological measurements included wind speed, air temperature, and relative humidity observed at several heights above the canopy sampling occurred at 1 sec and 5 min intervals. These measurements were used to calculate wind speed, air temperature, and relative humidity profiles down to the top of the grass canopy. Analysis of the measured thermal images consists of quantifying the diurnal thermal differences in the directional background signatures, directional thermal variance, and thermal variance differences related to observation angle, solar radiation, and wind speed. These preliminary analyses indicate that for this environment, measurements at large temporal scales, the thermal variance is primarily affected by solar radiation, but at small temporal scales turbulent mixing of fluxes becomes the more dominant cause of the variance.

An electromagnetic scattering solution for the interaction between the perfect conducting plate and the 1-D conducting slightly rough surface is presented in this paper. Taking the advantage of a newly developed technique that utilizes the reciprocity theorem, the difficulty in formulating the secondary scattered fields from the composite target reduces to the evaluation of integrals involving the polarization currents of the conducting plate and the scattered fields from the slightly rough surface. This method used in this paper can avoid the complex evaluation if scattering field under non-planar wave illustrated when calculating the secondary scattering fields. The polarization currents of the conducting plate is evaluated by using Physic Optics (PO) method, and the scattering fields from the slight rough surface are evaluated by using the SPM method. The results obtained have been analyzed in detail.