Camouflage performance of winter uniforms: photosimulations in the visual spectrum

Abstract

Minimizing electro-optical signatures of soldiers against modern sensors is a challenging task, but a task with high importance and benefits for operative soldiers that need to stay undetected. Optimizing camouflage uniforms for winter conditions efficiently reduces soldier signatures in winter scenes, especially in the visual spectrum. Snow usually dominates winter scenes and is difficult to mimic because the spectral properties of snow change with several parameters such as grain size, structure, and wetness. Developing efficient winter camouflage thus requires knowledge and data on the spectral properties of snow. This paper presents spectral data on common snow types in Norway and evaluates the camouflage performance of several winter uniforms of different colors and patterns. We assessed and ranked the camouflage performance of the uniforms quantitatively in the visible spectrum using an observer-based photosimulation where many soldiers searched for targets in various Norwegian winter scenes. By collecting a large number of detection times, indicating how difficult it was for an observer to detect each camouflage in each of the unique winter scenes, it was possible to rank the camouflage targets quantitatively. The results show how each camouflage performed (given by time of detection or as a percentage) compared to all the other camouflages in the test for each scene. The photosimulation method is time-consuming, but it gives a realistic estimation of camouflage performance over the different scenes. We discuss the performance of the various winter camouflages with their pattern and similarity to snow (color coordinates).