Intelligent radar radiation source signal classification method based on long-short time memory model

Abstract

The invention discloses an intelligent radar radiation source signal classification method based on a long-short time memory model. The method mainly solves the problem that the prior art is low in identification rate and slow in identification speed. The realization scheme is as follows: 1) generating a radar radiation source signal data set, and performing data preprocessing on the same; 2) acquiring a training sample set, a testing sample set and a verification sample set from the preprocessed data set; 3) constructing a seven-layer long-short time memory unit network and setting parametersof a network model; 4) adjusting the hyper-parameter of the network model and training the long-short time memory unit network by utilizing the training sample set and the testing sample set; and 5)inputting the verification sample set into the trained long-short time memory unit network model, thereby acquiring a radar radiation source signal classification result. Through the classification method disclosed by the invention, the automatic feature extraction and accurate signal classification can be performed on the one-dimensional signal; and the classification result is excellent, the time complexity is low, the stability is good, and the method can be used for the radar radiation source signal identification under the complex electromagnetic environment.

Description

technical field [0001] The invention belongs to the technical field of signal processing, in particular to a radar-based radiation source identification method, which can be used in electronic intelligence reconnaissance, electronic support and threat warning systems. Background technique [0002] Radar emitter signal identification is an important part of radar electronic countermeasures, and plays an important role in electronic intelligence reconnaissance, electronic support and threat warning systems. [0003] In the field of military communication countermeasures, it is generally necessary to jam and intercept enemy communications. The identification and classification of radar radiation source signal modulation is the first problem to be faced in jamming and interception. In the field of civil communications, radio spectrum detection and management, radar signal confirmation, and signal interference identification all require signal identification technology. With the...

AI Technical Summary

Problems solved by technology

However, there are two shortcomings in these existing technologies: the first is that the algorithm recognition rate is low

That is to say, most of the existing algorithms rely on artificially selected features, and the quality of the features determines the recognition rate, which cannot adapt to the increasingly complex electromagnetic environment.

The second disadvantage is the high time complexity

Now with the continuous increase of data dimension, the recognition time of existing algorithms is getting longer and longer, which cannot be applied to systems with high real-time requirements

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