Method and device for radar jamming identification based on convolutional neural network

Abstract

The present invention relates to a radar interference identification method and device based on a convolutional neural network. The method uses the radar to provide the spatiotemporal parameters (such as azimuth, distance, time, etc.) The identification of various types of interference helps combat commanders identify interference. It has the characteristics of strong adaptability, fast decision-making speed, and high robustness and fault tolerance.

Description

technical field [0001] Embodiments of the present invention relate to the field of radar countermeasures, in particular to a method and device for identifying radar interference based on a convolutional neural network. Background technique [0002] As an important military equipment for battlefield reconnaissance, surveillance and intelligence collection, radar is the core equipment for obtaining information and precise guidance on the battlefield. Especially in a vast combat area, it can obtain various target information in a timely, accurate and comprehensive manner. The role of radar is irreplaceable. Destroying the normal operation of the radar also destroys the important information source of the entire weapon system. [0003] At the same time, in the information warfare, the battlefield space is unprecedentedly expanded, the battlefield information is massive, the battlefield environment is complex, the combat objects are diversified, and the combat intensity is incre...

AI Technical Summary

Problems solved by technology

[0006] The traditional non-intelligent interference identification method based on human experience and cognition can no longer effectively cope with the rapidly changing battlefield and massive data. It has become a difficult problem to accurately and quickly obtain target information from massive radar detection data and identify radar interference

Images