DETECTION AND OBSERVATION OF HIGH-ALTITUDE SPACE OBJECTS USING THE MULTI-VIEW OBSERVATION ALGORITHM

Abstract

Based on the results of the conducted research, it is shown that the operational refinement of the space surveillance catalog with data on the parameters of the orbits of, high-altitude object (HAO) can be provided using early-warning radars (EW radar). Increased radar detection when working on HAO is possible by increasing the station's capacity or increasing the duration of observation. The increase in potential is directly related to the creation of new powerful energy-consuming radars. It is established that the increase in observation time is possible without significant material costs. This boils down to the development and implementation of long-term (multi-view) surveillance methods, which are called "track-before-detect" (TBD) in modern technical literature. When using them, the decision about the presence of a target is not made in each individual review, and tracking algorithms are used to detect moving objects. The principal possibility of extending the radar range when detecting and measuring the parameters of the trajectory of the HAO is proved due to the joint processing of the results of several soundings. An algorithm for detecting and tracking HAO is proposed. It is based on incoherent accumulation of signal information from several probes and transformation of the information into a parametric space. Then, search for and evaluate the parameters of their trajectories. That the use of such an algorithm does not lead to the need to increase the power potential of the radar. It shows the disadvantages that prevent the implementation of the algorithm as the main one, and the possibility of its application as an additional one in the path of radar information processing. The quality of trajectory information obtained during multi-view observation is analyzed. It is established that when using multi-view block-type observation methods, the necessary quality of preliminary estimation of trajectory parameters is provided by simultaneous processing of a set of measurements. An additional source of errors may be the probabilistic nature of selecting marks of the detected trajectory for subsequent estimation of its parameters.