Methodology of object detection, coordinate determination and selection in the process of front zone framing in a two-position airborne control system

Problem statement. Operational acquisition of reliable and highly informative data from aviation systems in the modern world plays a very important role. At the same time, high-resolution frames are required not only to be generated, but also to be intelligently analyzed, for example, on the basis of neural network approaches in order to ensure a high level of automation of the aviation control system as a whole. The process of automatic recognition of objects of interest involves three processing steps, namely detection, selection and recognition itself. In this chain, an important step is the detection of real targets on the RLC, which is one of the most difficult areas of research in the field of RLC sequence formation. For the realization of each of the listed tasks, requires a certain number of operations in the processing of collected data, and therefore the time of realization of the above list of tasks is growing, which is a problem because the time of their overall realization is required to reduce. Objective. To develop and investigate the method of forming a sequence of high-resolution RLC with parallel realization of algorithms of detection, selection, recognition, determination of FNO coordinates, as well as parameters of their movement in the process of formation of each frame with ensuring high accuracy of reliability and completeness of the formed data on FNO, located in the zone with emergency situation. Results. The methodology of formation of high-resolution radar frames in the front line of sight of each radar with parallel implementation of the processes of detection, selection and recognition of ground objects of interest from the determination of their coordinates, as well as the parameters of their motion by the end of frame formation has been developed in order to increase the speed of the system as a whole and minimize the time-of-flight task execution. Practical significance. The proposed methodology can be used in the search for people and physical ground objects (PGO) in emergency zones, in the assessment of ice fields, in the control of natural and man-made objects, interpretation of fires, structural and seasonal changes, etc.