Complexing of information channels of UAV detection and observation systems from the statistic solutions theory standpoint

Abstract

Currently, unmanned aerial vehicles (UAVs) provide a wide range of useful tasks for humanity, but, on the other hand, they pose a serious threat in economic, military and other areas of human activity. Difficulties in observing UAVs using modern technical means, as well as their relatively low cost, lead to an expansion of the scope of UAVs based illegal actions. Therefore, the protection of various objects against UAVs is a serious scientific and technical task of today. Since the possibilities of the known methods of UAV detection are different, the joint use of systems of different types is realized in practice nowadays, in order to increase the informativeness of the obtained data by their joint (complex) processing. The number of publications in this field is constantly increasing, and considerable attention is paid to integrated systems built on the basis of various physical sensors. However, the efficiency of multi-sensor systems with integrated processing of the output signals of the channels in practice remains insufficient. This article is devoted to the study of methods for the synthesis of new, more efficient algorithms for complexing radar, acoustic, optical and infrared information channels of integrated UAV detection and recognition systems, which are performed from the standpoint of statistical theory of radio system optimization. This approach allows synthesizing the optimal (according to the selected quality criterion) complex information processing system, which ensures obtaining the maximum amount of information from the vector process observed at the inputs of information channels. There shown the possibility of constructing an optimal UAV detector with the use of the late strategy of combining information at the level of decisions made in individual channels of the system.