<title>Sensor-based validation of synthetic thermal scenes: how close is good enough?</title>

Abstract

Using synthetic background scenes in the modeling of thermal infrared sensor-based smart munitions offers tremendons flexibility in exploring the performance envelope of these systems. However, to reach this goal, the synthetic background generation process must undergo the scrutiny of verification and validation to be accredited for use with a specific sensor system. Traditional approaches to validating synthetic scenes range from low-level subjective comparison to absolute pixel-to-pixel agreement between the two scenes. Neither of these approaches considers the specific smart munition sensor and processor which ultimately use the scene. In this paper we present an alternate validation approach based on comparison between end performance of a thermal infrared sensor-based smart munition system using synthetic/real scene pairs. Paired synthetic/real thermal scenes, including a low and a high-clutter level, are compared with conventional validation metrics and with the performance-based metric, using various smart munition sensor targeting algorithms. The degree of scene fidelity (absolute agreement between scene pairs) required to replicate performance varies with clutter level and processor algorithm. Under high clutter conditions, greater synthetic scene fidelity is required to match performance.Keywords: Synthetic background scenes, sensor-based validation 1. BACKGROUND The high cost of "live fire" and "full up" testing of smart munition systems has motivated the development of simulation-based alternatives to performing physical hardware testing. A variety of simulation techniques exist. Hardware-in-the-loop simulation consists of "injecting" a signal behind the sensor to test functioning of the actual hardware system. Typically the injected signal is obtained from captive flight data of actual targets in background. A digital simulation of the hardware sensor can be used in place of actual hardware. An example of this approach is embodied in the TOPATTACK 2 TOPATTACK is a configurable engineering-level model of a thermal infrared-based smart munition sensor that simulates flight, scanning dynamics, optics, atmospheric effects, detector, and electronic components. It is currently being used to simulate the performance of developing and conceptual smart munition systems.3 In this application the sensor munition "flies" over a measured thermal background scene containing a separately measured thermal image of a target. The output voltage serves as input to the targeting algorithm, which determines the weapon's response. The time of the response can then be mapped into the target coordinate system to determine aimpoint or hitpoint location (i.e. performance) for the engagement.It is Army policy that all models used for cost and operational effectiveness analysis be deemed acceptable for that specific application. This determination, termed accreditation, signifies that the appropriate test and evaluation agency judges the model to be adequate for its intended use based on experience, expert judgment, and a revi...

Methodology of real-time simulation to support field testing of dual-mode smart munitions sensors

“…The three main models of this process are TopAttack Version 1.0, Radiance, and the profilometer model. The model TopAttack Version 1.0 has been described in great detail 10,1 , validated 11,2,12 , and used extensively for smart munition simulations 13,14,15 . The laser profilometer model 3 is a new detailed sensor model that simulates the hardware, optics, and range detection used by the laser profilometer on the AH sublet.…”

<title>CAMEO-SIM: a broadband scene generation system that is fit for purpose</title>

“…= inband radiance 01 = incidence angle between source and reflector J(X) = source intensity (W/sr) 8(X) = sensor spectral response p"(X) = spectral bi-directional reflectivity 5 = distance to the source…”