The photosimulation test is one of preferred method to evaluate the effectiveness of the camouflage cover. The arrangement of the photosimulation test is in principal similar to the way of testing the target acquisition performance. The deal of this paper is to refer about our experiences with the application of methods of target acquisition performance to the results of the robust set of the photosimulation trials.
Nowadays, there is wide spectrum of areas of use of small unmanned aerial vehicles (UAV, drones). Their low cost, flexibility of use, low service cost and independence on infrastructure make them ideal carriers of different cargo. This fact brings many significant safety risk and threats. Especially aerial survey, flight zones disruptions and transport dangerous cargo. Above mentioned threat can be eliminated by: disabling navigation and control features, taking control over the steering and object destruction. One of the possible typically military solutions of that situation, is destruction by shooting. The most common way of solving the above task, is the use of barrel weapons of individual shooter or small military units. Therefore, we focused our effort on preventing the UAV mission accomplishing by its shooting destruction. To accomplish the task, in addition to detection and identification, we consider the distance determination as a fundamental problem. For the purposes of this paper, the distance determination we consider as a “localization”. Comparison of UAV localization options is the issue of this paper. Two localizations methods have been defined. Localization option include active method (ILR – impulse laser rangefinder) and passive method (triangulation method). Using mathematical modelling we proved, that ILR measurement is possible. To determine a distance with a defined probability we designed specific measurement frequency. For a predetermined type of UAV and ILR we identified the maximum distance that can be measured. In the second part of this paper, we analyzed the accuracy of localization using the triangulation method. The accuracy of localization using this method is dependent on the squared of the UAV distance. There are two significant advantage of this method: measurements can be made continuously and multiple objects in the field of view can be measured at the same time. This article is part of a planned publishing activity dealing with the issue
Physical characteristics of camouflage patterns such as color or remission spectra can be tested and measured by objective methods. In the vast majority of use of camouflage pattern, the human (obscure person) will recognize the camouflaged object. Therefore, the quality of the camouflage pattern ultimately determines how a person in a given environment perceives the camouflage pattern. Human perception is very subjective, and its assessment cannot be measured by simple physical methods. Therefore, we process the observer’s visual performance when searching for camouflaged objects. It must always be based on the statistical processing of information on perceived quality of camouflage by individual observers. One of the methods for assessing the quality of camouflage surfaces is so called observer test. The observer test is a simple visual test in which a number of viewers observe a series of images of different scenes containing camouflaged object. The time taken to find the camouflaged object is measured. Depending on the time, it takes to find the camouflaged object, the quality of the camouflage pattern is judged. The time required to find a camouflaged object depends, among other, on the arrangement of the scene, the conditions of the observer test, how the observer interacts with the test interface, the observer's properties and last but not least the camouflage pattern quality. The time taken to find a camouflaged object by a particular observer in a particular frame must be assumed as a random variable because it depends on a large number of independent factors. The rated quality of the camouflage pattern is only one of these factors. Among the others, it was aim of the experiment we performed to evaluate the statistical behavior of the random variable to be able to describe the behavior of it by a suitable type of distribution.
This article focuses on results of international measurement that took place in a military training area near Baad Shaarow in the summer of 2017. The main goal of this measurement was collecting information about current attitudes to camouflage targets detection. Participants measured spectral signatures of present targets by using hyperspectral sensors. Image spectroscopy has been in great demand for the last decade. This field was initially used in remote sensing application. The progress in electrotechnology allowed for spreading out into diverse branches. This system has not been used in military technology for too long. The military application involves specific tools. This event was attended by several research groups from several countries. Every group operated a different hyperspectral device and they documented an identical target. Using different devices there was a wide spectrum of apparatus which work in different spectrum from VIS to SWIR. The main part of this work is focused on hyperspectral data comparison.
Traditionally spectral reflectance of the material is measured and compared with permitted spectral reflectance boundaries. The boundaries are limited by upper and lower curve of spectral reflectance. The boundaries for unique color has to fulfil the operational requirements as a versatility of utilization through the all year seasons, day and weather condition on one hand and chromatic and spectral matching with background as well as the manufacturability on the other hand. The interval between the boundaries suffers with ambivalent feature. Camouflage pattern producer would be happy to see it much wider, but blending effect into its particular background could be better with narrower tolerance limits. From the point of view of long time user of camouflage pattern battledress, there seems to be another ambivalent feature. Width of the tolerance zone reflecting natural dispersion of spectral reflectance values allows the significant distortions of shape of the spectral curve inside the given boundaries.
The usage small-unmanned aerial vehicles (UAVs) is significantly increasing nowadays. They are being used as a carrier of military spy and reconnaissance devices (taking photos, live video streaming and so on), or as a carrier of potentially dangerous cargo (intended for destruction and killing). Both ways of utilizing the UAV cause the necessity to disable it. From the military point of view, to disable the UAV means to bring it down by a weapon of an ordinary soldier that is the assault rifle. This task can be challenging for the soldier because he needs visually detect and identify the target, track the target visually and aim on the target. The final success of the soldier’s mission depends not only on the said visual tasks, but also on the properties of the weapon and ammunition. The paper deals with possible methods of prediction of probability of hitting the UAV targets.
Pixelated camouflage patterns fulfill the role of both principles the matching and the disrupting that are exploited for blending the target into the background. It means that pixelated pattern should respect natural background in spectral and spatial characteristics embodied in micro and macro patterns. The HS imaging plays the similar, however the reverse role in the field of reconnaissance systems. The HS camera fundamentally records and extracts both the spectral and spatial information belonging to the recorded scenery. Therefore, the article deals with problems of hyperspectral (HS) imaging and subsequent processing of HS images of pixelated camouflage patterns which are among others characterized by their specific spatial frequency heterogeneity.