Active night vision systems based on laser diodes emitters have now reached a technology level allowing military
applications. In order to predict the performance of observers using such systems, we built an analytic model including
sensor, atmosphere, visualization and eye effects. The perception task has been modelled using the Targeting Task
Performance metric (TTP metric) developed by R. Vollmerhausen from the Night Vision and Electronic Sensors
Directorate (NVESD). Sensor and atmosphere models have been validated separately. In order to validate the whole
model, two identification tests have been set up. The first set submitted to trained observers was made of hybrid images.
The target to background contrast, the blur and the noise were added to armoured vehicles signatures in accordance to
sensor and atmosphere models. The second set of images was made with the same targets, sensed by a real active sensor
during field trials. Images were recorded, showing different vehicles, at different ranges and orientations, under different
illumination and acquisition configurations. Indeed, this set of real images was built with three different types of gating:
wide illumination, illumination of the background and illumination of the target.
Analysis of the perception experiments results showed a good concordance between the two sets of images.
The calculation of an identification criterion, related to this set of vehicles in the near infrared, gave the same results in
both cases. The impact of gating on observer's performance was also evaluated.