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 (m<sup>2</sup>), the average and RMS variation in target<i> source </i>temperature, and the average and RMS variation in the <i>apparent</i> 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 <i>source</i> and <i>apparent</i> 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.