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2022
Conference Paper
Title
SIMTAD: a simulation tool for evaluating target detection performance of imaging systems
Abstract
Target detection is a crucial task in defense applications such as surveillance, infrared search and track, and missile approach warning systems. Typically, the target image is extended over a few sensor pixels of the imaging system only and the detection is performed by appropriate algorithms.
In order to study the impact of imaging system design parameters and environmental conditions on the detection performance, a simulation tool is developed. Apart from computing detection ranges based on the expected signal to noise ratio the algorithm requires for detection, the tool is also meant for simulating image sequences of engaging targets. Therefore, it provides means to investigate the interplay between system design parameters and algorithms for target detection.
The simulation is based on a rigorous calculation of the target image in the focal plane, with consideration of the optical transfer functions of imaging chain components. Integrating the target image over the active pixel areas yields the additional signal of the detector pixels caused by the target. Based on these values and average background noise the signal to noise ratio (SNR) is obtained as function of the target distance. Image data is generated by overlaying the additional signals over a background image.
We exemplify the application of the simulation tool by studying the effect of various system parameters and environmental conditions on the resulting SNR and detection range. Corresponding simulated image data is presented as well.
In order to study the impact of imaging system design parameters and environmental conditions on the detection performance, a simulation tool is developed. Apart from computing detection ranges based on the expected signal to noise ratio the algorithm requires for detection, the tool is also meant for simulating image sequences of engaging targets. Therefore, it provides means to investigate the interplay between system design parameters and algorithms for target detection.
The simulation is based on a rigorous calculation of the target image in the focal plane, with consideration of the optical transfer functions of imaging chain components. Integrating the target image over the active pixel areas yields the additional signal of the detector pixels caused by the target. Based on these values and average background noise the signal to noise ratio (SNR) is obtained as function of the target distance. Image data is generated by overlaying the additional signals over a background image.
We exemplify the application of the simulation tool by studying the effect of various system parameters and environmental conditions on the resulting SNR and detection range. Corresponding simulated image data is presented as well.