Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
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...
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...
That smart munitions false alarms result from randomly-spaced fixed position discrete physical objects within the background is the standard assumption for false target treatment in several smart munitions performance and effectiveness models. This premise is tested in a simulation study which identifies specific terrain features causing a hypothetical thermal infrared smart munitions sensor to false alarm. The sensor configuration and the target detection algorithms are input to the Waterways Experiment Station (WES) smart munitions sensor model which is "flown" over high resolution calibrated thermal imagery of several test sites for which there is ground truth. Target detection decisions in these target-free backgrounds are mapped into large scale color aerial photographs taken simultaneously with the thermal imagery. False alarm-causing terrain features are identified from the aerial photographs and are characterized as a function of test site, time of day, and target acquisition algorithm used. Several important characteristics of thermal false alarms are formulated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.