Multi-component radar signal intra-pulse modulation mode identification method

Abstract

The invention relates to the field of automatic recognition algorithms of deep learning, in particular to a multi-component radar signal intra-pulse modulation mode recognition method. The method comprises the following steps of acquiring time-frequency images of the single-component or overlapped multi-component radar signals of several different intra-pulse modulation modes; preprocessing the radar signal time-frequency image by using an image processing algorithm, and making a training set and a test set by using the signal type contained in the radar signal as a label; designing a pre-training network based on a convolutional neural network to extract radar signal time-frequency image features, and designing a multi-component signal classification network based on reinforcement learning to obtain a classification and recognition result; training, testing and perfecting a network structure and parameters; classification and identification of multi-component signals are realized. Themulti-component radar signal identification algorithm provided by the invention has a wide radar signal type application range and relatively high identification accuracy under the condition of low signal-to-noise ratio, and realizes intra-pulse modulation mode identification of randomly overlapped multi-component radar signals.

Description

technical field [0001] The invention relates to the field of automatic identification algorithms for deep learning, in particular to a method for identifying intrapulse modulation modes of multi-component radar signals. Background technique [0002] The identification of radar signal intrapulse modulation is an important link in modern electronic intelligence reconnaissance and electronic support systems. [0003] Due to the increasing density of radar signals in the modern electronic warfare environment, and most modern radar signals use pulse compression signals with large time widths, radar reconnaissance systems often intercept pulses that overlap in time domain to form multi-component radar signals. Most of the existing radar signal modulation identification technologies are not adaptable to the multi-component signal environment, resulting in signal identification errors or identification failures. Therefore, the analysis and processing of multi-component signals is a...

AI Technical Summary

Problems solved by technology

[0005]There are some problems in the identification methods of multi-component radar signals proposed at present: the identification method based on the feature extraction of signal transformation domain has limitations, and it is only for a certain type of specific signal Effective, but difficult to adapt to a wide range of radar signal types; the recognition effect of the recognition method based on multi-component signal separation is largely determined by the separation effect of the multi-component signal separation algorithm, but the separation algorithm currently proposed has poor anti-noise performance and computational complexity. Higher problems, and it is difficult to solve the multi-component signal separation problem of time-frequency domain overlap, these problems will limit the recognition ability of the algorithm

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