Decorrelation Method for Passive Interference Signals in the Selection System of Slow-Moving Targets

Abstract

The wide range of small unmanned aerial vehicles (UAVs) capable of hovering in space, moving at low speeds and at low altitudes, has led to the emergence of a new class of complex radar objects. This, in turn, has led to the development of new radar stations, specifically their main nodes, such as the system for selecting slow-moving targets. Its main purpose is to distinguish moving radar objects (UAVs) against the background of passive interference, such as trees, poles, the earth's surface, hydro and meteorological formations, and so on.

This article analyzes research and publications demonstrating the approaches to solving the stated problem. The classical approach to implementing a moving target selection system based on first and second-order digital rejection filters is considered. Its advantages and disadvantages are outlined. New method for combating passive interference in a radar station using the Karhunen-Loève transform, which forms the basis of the principal component analysis data analysis method, is proposed. This method is used to reduce the dimensionality of the data set while retaining maximum energy (information) from the signal reflected from the moving target, while extracting information about stationary objects (data compression). An algorithm for building a moving target selection system for slow-moving targets is provided. The results of the operation of the moving target selection system based on the proposed method and the classical approach are investigated and illustrated. A comparative analysis of the impact of the moving target selection system on the power of the target echo signal is conducted. The dependence of the power of the target echo signal on its speed for the proposed method of selecting moving targets is plotted. Conclusions are drawn regarding the effectiveness of the system for low speeds.