Multi-station radar system interference identification method based on convolutional neural network

Abstract

The invention discloses a multi-station radar system interference identification method based on a convolutional neural network. The method comprises the following steps: obtaining K groups of slow-time random complex envelope sequences according to K radars in a multi-station radar system; horizontally linking the K groups of slow-time random complex envelope sequences in sequence to obtain a first two-dimensional data block; inputting the first two-dimensional training data block into a first interference discrimination network to obtain a first classification output result; adopting a gradient descent method to obtain a minimum value of a loss function of the first interference discrimination network so as to obtain a second interference discrimination network; inputting the first two-dimensional data block into a second interference discrimination network, and obtaining a third interference discrimination network when the error sum of the second interference discrimination network is smaller than or equal to a threshold value; inputting the second two-dimensional data block into the third interference discrimination network to obtain a final classification output result. According to the interference identification method, the utilization rate of sampling data in the information processing process of the multi-station radar system is improved, and the identification probability of deception interference is improved.

Description

technical field [0001] The invention belongs to the technical field of radar, and in particular relates to a multi-station radar system interference identification method based on a convolutional neural network. Background technique [0002] With the increasingly complex electromagnetic environment in modern warfare, effective electronic jamming countermeasure technology has become particularly important for radar systems. Among the many types of interference, deceptive interference is an important type of interference that the radar system needs to deal with. The intercepted radar signal is stored, modulated and forwarded, so that a large number of deceptive false targets are generated near the real target to interfere and confuse the radar. Detection system and tracking system. [0003] For deceptive interference, it is difficult for single-station radars to counteract, while a multi-radar system forms a networked detection system by connecting the radars at each spatiall...

AI Technical Summary

Problems solved by technology

The strong model learning and feature representation capabilities of convolutional neural networks are used to identify deceptive jamming, which makes up for the problems of single manual extraction features and unsatisfactory identification effects, and improves the probability of identifying deceptive jamming in multi-station radar systems.

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