The effects of Hull Film Cooling (HFC) water-spray systems on infrared detection have already been presented by Vaitekunas and Kim (,). This paper will further assess the impact of zonal Active Hull Cooling (AHC) water-spray systems on the infrared detection of naval ships to ensure its proper usage against a range of infrared-guided anti-ship missiles. The transient performance of such systems will also be assessed using a fully transient version of ShipIR/NTCS which includes a laminar flow water-film convection model to simulate the effects of an activated water-spray. The model can be used to analyse the performance of a proposed design, and adjust the nozzle count to meet a specific requirement. Recent efforts to validate the new model against existing experiments is also described.
A key component in any image-based tracking system is the adaptive tracking algorithm used to segment the image into potential targets, rank-and-select the best candidate target, and gate the selected target to further improve tracker performance. Similarly, a key component in any soft-kill response to an incoming guided missile is the flare/chaff decoy used to distract or seduce the seeker homing system away from the naval platform. This paper describes the recent improvements to the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR). Efforts to analyse and match the 3D flare particle model against actual IR measurements of the Chemring TALOS IR round resulted in further refinement of the 3D flare particle distribution. The changes in the flare model characteristics were significant enough to require an overhaul to the adaptive track gate (ATG) algorithm in the way it detects the presence of flare decoys and reacquires the target after flare separation. A series of test scenarios are used to demonstrate the impact of the new flare and ATG on IR tactics simulation.
A key component in any soft-kill response to an incoming guided missile is the flare /chaff decoy used to distract
or seduce the seeker homing system away from the naval platform. This paper describes a new 3D flare particle model in
the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR), which provides
independent control over the size and radial distribution of its signature. The 3D particles of each flare sub-munition are
modelled stochastically and rendered using OpenGL z-buffering, 2D projection, and alpha-blending to produce a unique and
time varying signature. A sensitivity analysis on each input parameter provides the data and methods needed to synthesize
a model from an IR measurement of a decoy. The new model also eliminated artifacts and deficiencies in our previous model
which prevented reliable tracks from the adaptive track gate algorithm already presented by Ramaswamy and
Vaitekunas (2015). A sequence of scenarios are used to test and demonstrate the new flare model during a missile
Existing FLIR detection models such as NVThermIP and NV-IPM, from the U.S. Army Night Vision and Electronic Sensors Directorate (NVESD), use only basic inputs to describe the target and background (area of the target, average and RMS temperatures of both the target and background). The objective of this work is to try and bridge the gap between more sophisticated FLIR detection models (of the sensor) and high-fidelity signature models, such as the NATO-Standard ShipIR model. A custom API is developed to load an existing ShipIR scenario model and perform the analysis from any user-specified range, altitude, and attack angle. The analysis consists of computing the total area of the target (m2), the average and RMS variation in target source temperature, and the average and RMS variation in the apparent temperature of the background. These results are then fed into the associated sensor model in NV-IPM to determine its probability of detection (versus range). Since ShipIR computes and attenuates the spectral source radiance at every pixel, the black body source and apparent temperatures are easily obtained for each point using numerical iteration (on temperature), using the spectral attenuation and path emissions from MODTRAN (already used by ShipIR to predict the apparent target and background radiance). In addition to performing the above calculations on the whole target area, a variable threshold and clustering algorithm is used to analyse whether a sub-area of the target, with a higher contrast signature but smaller size, is more likely to be detected. The methods and results from this analysis should provide the basis for a more formal interface between the two models.
A key component in any image-based tracking system is the adaptive tracking algorithm used to segment the image into potential targets, rank-and-select the best candidate target, and the gating of the selected target to further improve tracker performance. This paper will describe a new adaptive tracker algorithm added to the naval threat countermeasure simulator (NTCS) of the NATO-standard ship signature model (ShipIR). The new adaptive tracking algorithm is an optional feature used with any of the existing internal NTCS or user-defined seeker algorithms (e.g., binary centroid, intensity centroid, and threshold intensity centroid). The algorithm segments the detected pixels into clusters, and the smallest set of clusters that meet the detection criterion is obtained by using a knapsack algorithm to identify the set of clusters that should not be used. The rectangular area containing the chosen clusters defines an inner boundary, from which a weighted centroid is calculated as the aim-point. A track-gate is then positioned around the clusters, taking into account the rate of change of the bounding area and compensating for any gimbal displacement. A sequence of scenarios is used to test the new tracking algorithm on a generic unclassified DDG ShipIR model, with and without flares, and demonstrate how some of the key seeker signals are impacted by both the ship and flare intrinsic signatures.
A key input to any thermal infrared signature model is the environment, more specifically the model inputs specific to the thermal infrared background model. This paper describes a new method of analysing the climatic data for input to ShipIR. Historical hourly data from a stationary marine buoy are used to select a small number of data points (N=100) to adequately cover the range of statistics (CDF, PDF) displayed by the original data set (S=46,072). The method uses a coarse bin (1/3) to subdivide the variable space (35=243 bins), and a single-point ranking system to select individual points so that uniform coverage (1/N = 0.01) is obtained for each variable. The selected data points are used in Vaitekunas and Kim (2013) to demonstrate how the new methodology is used to provide a more rigorous and comprehensive analysis of platform IR susceptibility based on the statistics of IR detection.
A methodology for analysing the infrared (IR) signature and susceptibility of naval platforms using ShipIR/NTCS was presented by Vaitekunas (2010). This paper provides three key improvements: use of a larger climatic data set (N=100), a new target sub-image algorithm eliminating false detections from pixel-aliasing at the horizon, and a new seeker model interfacing with a line-by-line background clutter model. Existing commercial stealth technologies (exhaust stack suppression, low solar absorptive paints, extended hull film-cooling) are re-analysed using the new models and methods to produce a more rigorous and comprehensive analysis of their effectiveness based on the statistics of reduction in IR susceptibility. These methods and results combined with the cost of each stealth option should allow platform managers to select an appropriate level of infrared suppression and establish the design criteria for a new ship.
Most existing platform signature models use semi-empirical correlations to predict flow convection on internal and
external surfaces, a key element in the prediction of accurate skin signature. Although these convection algorithms are
capable of predicting bulk heat transfer coefficients between each surface and the designated flow region, they are not capable
of capturing local effects such as flow stagnation, flow separation, and flow history. Most computational fluid dynamics
(CFD) codes lack the ability to predict changes in background solar and thermal irradiation with the environment and sun
location, nor do they include multi-bounce radiative surface exchanges by default in their solvers. Existing interfaces between
CFD and signature prediction typically involve a one-directional mapping of CFD predicted temperatures to the signature
model. This paper describes a new functional interface between the NATO-standard ship signature model (ShipIR) and the
ANSYS Fluent model, where a bi-directional mapping is used to transfer the thermal radiation predictions from ShipIR to
Fluent, and after re-iteration of the CFD solution, transfer the wall and fluid temperatures back to ShipIR for further
refinement of local-area heat transfer coefficients, and re-iteration of the ShipIR thermal solution. Both models converge
to an RMS difference of 0.3 °C within a few successive iterations (5-6). This new functional interface is described through
a detailed thermal/IR simulation of an unclassified research vessel, the Canadian Forces Auxiliary Vessel (CFAV) Quest.
Future efforts to validate this new modelling approach using shipboard measurements are also discussed.
Methods of analysing the signature and susceptibility of naval platforms to infrared detection are described. An
unclassified ShipIR destroyer model is used to illustrate the primary sources of infrared signature and detection: the exhaust
system, solar-heating, and operating climate. The basic detection algorithm used by the Naval Threat Countermeasure
Simulator (NTCS) component of ShipIR is described and used to analyse the effectiveness of various stealth
technologies: stack suppression, low solar absorptive (LSA) paints, and Active Hull Cooling (AHC). Standard marine
climate statistics are used to determine a minimum (5%), average (50%) and maximum (95%) signature condition for each
operating region. The change in detection range of two wave-band sensors (3-5μm, 8-12 μm) operating at different altitudes
(10m, 270m) in each of four climatic conditions is used to assess the effectiveness of each stealth solution, providing a more
integral approach to infrared stealth design. These tools and methods form the basis on which future platform designs are
Proc. SPIE. 7300, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XX
KEYWORDS: Data modeling, Reflection, Reflectivity, Surface roughness, Bidirectional reflectance transmission function, Surface properties, High dynamic range imaging, Analytical research, System on a chip, Thermal modeling
A new standard for the measurement and analysis of optical surface properties for input to the ShipIR
model (Vaitekunas, 2002) are developed and tested using paint specimens taken from the unclassified Canadian research
vessel (CFAV Quest). The theory and equations used to convert the in-lab surface property measurements into ShipIR model
input parameters are described. The resultant data consists of two thermal model input parameters, solar absorptivity (αs) and thermal emissivity epsilon;Τ), and a series of in-band surface properties, the nominal emissivity (ε), nominal specular
reflectance (ρs), angular lobe-width (e) and a grazing-angle (b) parameter. Original sample measurements in 2004 are
supplemented with new hemispherical directional reflectance (HDR) and bi-directional reflectance distribution function
(BRDF) measurements in 2008 to track the changes in the paint specimens and expand the analysis to include additional input
parameters to ShipIR. A more rigorous treatment of the BRDF model relates the HDR and BRDF measurements to a single
surface roughness parameter (σ).
Modelling the bi-directional reflectance distribution function (BRDF) of a ship surface is an integral part of any
infrared ship signature model. The ShipIR surface BRDF model is based on Sandford and Robertson (1985) and makes a discrete assumption for lobe-width and solar-glint. The ShipIR sea surface reflectance model uses a roughness model based on the early work of Cox and Munk (1954) and refined using the integral solution proposed by Mermelstein et al. (1994). A similar approach was used by Ward (1992) to model the visual properties of a real surface, considering isotropic and anisotropic surface roughness. This paper compares the two roughness models and shows how a slope probability density
function (PDF) version of the bi-directional reflectance is better suited for modelling micro-faceted surface reflections. The simulation of an actual ship IR glint measurement demonstrates the effect of BRDF lobes in the paint property and provides a qualitative assessment of the ShipIR model.
The naval ship infrared signature model and naval threat countermeasure simulator (ShipIR/NTCS) developed by W.R. Davis Engineering Ltd has undergone extensive validation since its adoption as a NATO-standard, and has been accredited by the US Navy for Live Fire Test and Evaluation of the DDG class warship, Preliminary Design of the DD(X) destroyer, and Contract Design and Live Fire Test and Evaluation of DD(X). Validation has played a key role in the model development by assessing current accuracy, identifying key areas of improvement, and tracking achievements made by each new release. This paper describes some of the recent improvements in full-ship infrared (IR) signature measurement and model prediction based on the measurements and predictions of an unclassified Canadian research vessel (CFAV Quest). The results show how some of the more recent trial parameters: radiosonde input, ship surface optical properties, atmosphere-scattered solar irradiation, and large-scale Reynolds Number; have affected our model predictions and accuracy.
A signature model called SHIPIR was developed by W. R. Davis Engineering Ltd (DAVIS) and the Defence Research Establishment Valcartier (DREV). The IR scene component of the model incorporates a full-hemispherical background, the ability to define multiple ship targets, each with their own exhaust plume and flare decoy deployments, and an interactive engagement simulation with an IR observer or seeker model. The model runs on an entry-level Silicon Graphics (SGI) workstation. The program relies on the color image display for both signature analysis and to drive the engagement model. To achieve reasonable refresh rates and meet the necessary image resolution requirements, a unique set of display routines had to be devised to enhance the basic capabilities of the OpenGL graphics library. These routines, which include a multiple clipping plane algorithm, sub-image analysis, transparent plume-gas rendering, and automatic threshold detection, are described. Methods for predicting and assessing the image accuracy of a generic ship model are presented. Shortcomings of running the software on an Intel-based PC are also discussed.
An integrated naval infrared target, threat and countermeasure simulator (SHIPIR/NTCS) has been developed. The SHIPIR component of the model has been adopted by both NATO and the US Navy as a common tool for predicting the infrared (IR) signature of naval ships in their background. The US Navy has taken a lead role in further developing and validating SHIPIR for use in the Twenty-First Century Destroyer (DD-21) program. As a result, the US Naval Research Laboratory (NRL) has performed an in-depth validation of SHIPIR. This paper presents an overview of SHIPIR, the model validation methodology developed by NRL, and the results of the NRL validation study. The validation consists of three parts: a review of existing validation information, the design, execution, and analysis of a new panel test experiment, and the comparison of experiment with predictions from the latest version of SHIPIR (v2.5). The results show high levels of accuracy in the radiometric components of the model under clear-sky conditions, but indicate the need for more detailed measurement of solar irradiance and cloud model data for input to the heat transfer and in-band sky radiance sub-models, respectively.
An integrated naval infrared target, countermeasure and threat model is presented. The target modeling capabilities include complex 3-D surface geometries, a thermal system model with auto-generated solar heating, sea/air convection, sea/sky radiation and inter-surface radiation, a surface radiance model which accounts for multiple diffuse reflections, observer-to-target atmospheric absorption and path radiance, and an exhaust gas dispersion and IR emission model. The IR images of any number of targets can be rendered simultaneously within a full-hemispherical sea/sky/sun background relative to an observer at a specified altitude, based on the atmospheric radiance, solar irradiance, path radiance and time-average solar sea-glint. Flare countermeasures are added to the scenario through definition of canisters, submunitions, burn characteristics and deployment tactics. The IR missile model has been constructed from a minimum number of parameters to keep the model generic and provide a reasonable estimate of IR susceptibility. The purpose of the model is to provide the tools necessary to develop and assess the effectiveness of infrared signature suppression and infrared countermeasures. A number of analysis methods are provided, including on- screen image analysis, polar signature plots, polar lock-on range and engagement simulation.
A Canadian Naval threat/countermeasures simulator (NTCS) capable of modeling the engagement between a naval ship and an infrared (IR) guided anti-ship missile is presented. The NTCS program is built upon previously developed naval ship signature software entitled Ship Infrared Simulator (SHIPIR) which produces 3-D graphical imagery of a ship in its sea/sky background for a wide range of operational, atmospheric, observer, and spectral conditions. By adding models for an IR seeker head, missile flight dynamics and commonly deployed ship IR countermeasures, NTCS can effectively assess the IR susceptibility of naval platforms through calculation of target lock-on ranges and hit/miss distances. Current and future naval ships can be analyzed for IR suppression effectiveness in such areas as hot surface visibility, low emissivity paints, and engine exhaust signature suppression. The various deployable countermeasures (flares, smoke screens, washdown, and ship maneuvers) and missile/seeker heads modeled in NTCS permit the assessment of ship survivability and development of tactics and counter-measures necessary to provide adequate IR protection. A description of NTCS is provided with emphasis on the missile and countermeasure models and overall engagement simulation. Some sample simulations to date on the Canadian DDH-280 tribal class destroyer are presented.
SHIPIR is a model which simulates infrared images of ships at sea. The model is divided in five main modules. The ship model definition module defines the ship geometry, the thermal plates, the radiative surfaces, and the user-specified thermal boundary conditions. The simulation condition definition module gathers all necessary inputs to simulate a specific IR image. The background irradiance computation module runs Lowtran7 to compute atmospheric transmittance and radiance, direct solar irradiance and sea irradiance on the ship and the observer. The heat transfer solution is then computed with a steady-state algorithm, generating the ship surface temperatures. The infrared scene generation module creates the scene as viewed by an observer in a predefined waveband and at a position that can be changed interactively. A simple IR plume image is also generated at this stage. This paper describes the different modules that are part of the model. Examples of the outputs generated with a baseline scenario are given. The steps and results of a validation experiment performed with data from two instrumented plates are highlighted.