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The development and optimisation of modern infrared systems necessitates the use of simulation systems to create radiometrically realistic representations (e.g. images) of infrared scenes. Such simulation systems are used in signature prediction, the development of surveillance and missile sensors, signal/image processing algorithm development and aircraft self-protection countermeasure system development and evaluation. Even the most cursory investigation reveals a multitude of factors affecting the infrared signatures of realworld objects. Factors such as spectral emissivity, spatial/volumetric radiance distribution, specular reflection, reflected direct sunlight, reflected ambient light, atmospheric degradation and more, all affect the presentation of an object's instantaneous signature. The signature is furthermore dynamically varying as a result of internal and external influences on the object, resulting from the heat balance comprising insolation, internal heat sources, aerodynamic heating (airborne objects), conduction, convection and radiation. In order to accurately render the object's signature in a computer simulation, the rendering equations must therefore account for all the elements of the signature. In this overview paper, the signature models, rendering equations and application frameworks of three infrared simulation systems are reviewed and compared. The paper first considers the problem of infrared scene simulation in a framework for simulation validation. This approach provides concise definitions and a convenient context for considering signature models and subsequent computer implementation. The primary radiometric requirements for an infrared scene simulator are presented next. The signature models and rendering equations implemented in OSMOSIS (Belgian Royal Military Academy), DIRSIG (Rochester Institute of Technology) and OSSIM (CSIR & Denel Dynamics) are reviewed. In spite of these three simulation systems' different application focus areas, their underlying physics-based approach is similar. The commonalities and differences between the different systems are investigated, in the context of their somewhat different application areas. The application of an infrared scene simulation system towards the development of imaging missiles and missile countermeasures are briefly described. Flowing from the review of the available models and equations, recommendations are made to further enhance and improve the signature models and rendering equations in infrared scene simulators.

Radiometrically accurate simulation of InfraRed (IR) signatures is an essential prerequisite for valid IR sensor testing within the IR Scene Projection (IRSP) community. The Electronic Combat Stimulation (ECSTIM) Branch EO/IR Laboratory at the NAVAIR Air Combat Environment T&E Facility (ACETEF), NAWC-AD, Patuxent River, Maryland has recently begun validation testing of their Large Format Resistive-emitter Array (LFRA) IRSP. This is in preparation for developmental and operational testing of emerging mission-critical IR Countermeasure (IRCM) systems. Validation is guided by the Navy Air Defense Threat Simulator Validation Procedures Manual (NAWCWPNS TM 7489-3) and will support s other emerging high priority development programs such as the Joint Distributed IRCM Ground-test System (JDIGS). This paper discusses the ECSTIM/EO/IR Laboratory LFRA IRSP validation testing process, the resulting data collection, measurements and analysis.

For more than a decade US Army CERDEC Night Vision and Electronic Sensors Directorate (NVESD) has been developing real-time imaging infrared sensor simulations to aid the Army in: sensor design, prototyping, and analysis; search and target acquisition (STA) model development; and evaluation of tactics, techniques and procedures. In recent years, the sensor simulation program has undergone significant programmatic and technical changes, while still seeking to deliver simulation tools to the Army. This paper provides an update on the current state of NVESD simulation capabilities, the technical vision and the simulation validation efforts. Topics to be discussed include the transition of software to the PC platform, an explanation of the principle software products, and a look at future validation experiments and software enhancements.

The modeling and simulation community has developed many processes for certifying the creditability of simulation models. Many of these processes are implemented throughout the model development cycle and require comparison of the developed model with the system being simulated. With the increased focus on model reuse, these processes need to be tailored to address the development cycle of reusing existing creditable models. This paper outlines the validation process that certifies the creditability of simulation models produced by the MRMAide (Mixed Resolution Modeling Aide). MRMAide is a technology that semi-automates the development of model wrappers. These wrappers are used to resolve fidelity differences between models using mixed resolution modeling (MRM) techniques that allow for the reuse of existing simulation models. The MRMAide validation process extrapolates on existing processes that are implemented throughout the development cycle of a simulation model and addresses MRMAide's development processes.

The addition of an advanced EO subsystem to an in-service tracker system is reviewed in terms of the sensor modelling and proving activities. For the latter, emphasis is placed on model verification and validation techniques that will lead to a validation case which will then be used to gain equipment acceptance with the UK Royal Navy. The approach to modelling encompasses parametric and image-flow models. The relationship between these different representations is described together with their interaction with the EO equipment and the project development lifecycle. The algorithms generated for the image flow model will be used as the basis for the EO subsystem detection, tracking, and data association software. Issues arising from model validation activities are addressed in detail and include the validation approach, appropriate metrics, coverage of the operational envelope and the use of synthetic imagery to augment trials data.

While the military and commercial communities are increasingly reliant on simulation to reduce cost, the cost of developing simulations for their complex system may be costly in themselves. In order to reduce simulation costs, simulation developers have turned toward using collaborative simulation, reusing existing simulation models, and utilizing model abstraction techniques to reduce simulation development time as well as simulation execution time. This paper focuses on model abstraction techniques that can be applied to reduce simulation execution and development time and the effects those techniques have on simulation accuracy.

This paper describes infrared (IR) scene generation and validation activities at the U.S. Army Aviation and Missile Command's (AMCOM) Dual-Mode Hardware-in-the-Loop (HWIL) Simulation. The HWIL simulation validation results are based on comparison of infrared seeker data collected in the HWIL simulation to infrared seeker data collected during captive flight tests (CFTs). Use of CFT data allows a simulation developer to quantify not only the radiometric fidelity of the simulation inputs, but also the effects that any limitations of the inputs may have on simulation validity with respect to a particular seeker and its algorithms. Validation of this type of simulation is a complex process and all aspects of the validation are covered. Topics include real-time IR signature modeling and validation, simulation output verification, projected energy verification, and total end-to-end simulation validation. Also included are descriptions of the different types of CFT scenarios necessary for simulation validation and the comparison methodologies used for each case.

A realtime hardware-in-the-loop simulation facility for a multimode sensor is in use at the U.S Army Aviation and Missile Command's Advanced Simulation Center. The purpose of this facility is to simulate battlefield scenarios and generate performance data vital to the development and testing of such a system. The simulation has proven to be a cost- effective alternative to live-fire field tests and a valuable tool for performing engineering studies. A plan for verifying and validating the simulation has been developed and is currently being executed. The paper describes the simulation facility's role in the development and testing of a multimode sensor. Also presented are the simulation theory of operation and the target and environmental modeling methodologies employed in the laboratory. Finally, the simulation verification and validation (V&V) plan is outlined. In particular, the major challenges encountered thus far in the V&V process and the solutions devised to overcome them are described.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper presents the systematic approach used for the independent verification and validation of a Joint-Modeling and Simulation System (J-MASS) threat system model. Verification is the process of determining that a model implementation accurately represents the developers conceptual description and specifications. To minimize cost and maximize benefit, the verification process should parallel the model development process. It should begin with initial model development and continues throughout the model development process. This approach results in early identification of problems. These can be resolved cost effectively as the model development progresses instead of at the end of model development where cost for changes can be significant. When performing the verification tasks, the verification team reports frequently tothe program office and the model developer to assure that any findings are available for immediate action, and that verification activities are in consonance with program needs. The verification process is divided into the following verificationtasks: software requirements verification, engineering design verification (top level), detailed design verification (software design), system test support, documentation verification, software verification, and verification reporting. The valithtion process determines the degree to which a model is an accurate representation of the real world phenomenon from the perspective of the intended use(s) ofthe model. The objective of the validation effort is to document the differences between the model and the actual system that may impact the intended use of the model. To accomplish a validation effort in a timely manner and at minimum cost, the validation process should be integrated into the model development and model verification processes. The validation process consists of the following tasks: determine the model user requirements, establish the validation data baseline, develop a validation test matrix, test the model, compare model parametric test data to the validation data baseline, compare model performance data to the baseline, determine any impacts to model use that result from differences, and develop the model validation report. This paper outlines the procedures used to accomplish verification and validation of J-MASS models.

Techniques and tools for validation of real-time infrared target signature models are presented. The model validation techniques presented in this paper were developed for hardware-in-the-loop (HWIL) simulations at the U.S. Army Missile Command's Research, Development, and Engineering Center. Real-time target model validation is a required deliverable to the customer of a HWIL simulation facility and is a critical part of ensuring the fidelity of a HWIL simulation. There are two levels of real-time target model validation. The first level is comparison of the target model to some baseline or measured data which answers the question 'are the simulation inputs correct?' The second level of validation is a simulation validation which answers the question 'for a given target model input are the simulation hardware and software generating the correct output?' This paper deals primarily with the first level of target model validation.

Techniques and tools for validation of real-time infrared target signature models are presented. The model validation techniques presented in this paper were developed for hardware-in-the-loop (HWIL) simulations at the U.S. Army Missile Command's Research, Development, and Engineering Center. Real-time target model validation is a required deliverable to the customer of a HWIL simulation facility and is a critical part of ensuring the fidelity of a HWIL simulation. There are two levels of real-time target model validation. The first level is comparison of the target model to some baseline or measured data which answers the question `are the simulation inputs correct?'. The second level of validation is a simulation validation which answers the question `for a given target model input is the simulation hardware and software generating the correct output?'. This paper deals primarily with the first level of target model validation. IR target signature models have often been validated by subjective visual inspection or by objective, but limited, statistical comparisons. Subjective methods can be very satisfying to the simulation developer but offer little comfort to the simulation customer since subjective methods cannot be documented. Generic statistical methods offer a level of documentation, yet are often not robust enough to fully test the fidelity of an IR signature. Advances in infrared seeker and sensor technology have led to the necessity of system specific target model validation. For any HWIL simulation it must be demonstrated that the sensor responds to the real-time signature model in a manner which is functionally equivalent to the sensor's response to a baseline model. Depending on the application, a baseline method can be measured IR imagery or the output of a validated IR signature prediction code. Tools are described that generate validation data for HWIL simulations at MICOM and example real-time model validations are presented.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.