A radar emitter signal modulation identification method combined with multi-dimensional feature migration fusion

Abstract

The invention belongs to the field of electronic reconnaissance identification, in particular to a radar emitter signal modulation identification method combined with multi-dimensional feature migration fusion, comprising the following steps of generating nine kinds of radar signals to form a radar signal set; transforming the radar signal into time-frequency image by time-frequency transform; transforming the time-frequency image so as to meet the input requirements of the pre-trained large-scale network; sending the pre-processed time-frequency image to LeNet 5 network for feature extraction, and using the feature extraction module from input layer to form C5 convolution layer to output the feature extraction module; selecting a dimensionality reduction mode for the data obtained from the extracting feature step and processing the dimensionality reduction mode. The invention adopts the method of time-frequency analysis, maps the one-dimensional time-domain signal to the two-dimensional time-frequency domain, analyzes and processes the radar signal in the time-frequency domain, and has better effect for the non-stationary radar signal. The self-training network adopted by the invention has simple structure, and can improve the reliability of the system under the condition of low signal-to-noise ratio.

Description

technical field [0001] The invention belongs to the field of electronic reconnaissance identification, and in particular relates to a radar radiation source signal modulation identification method combined with multi-dimensional feature migration and fusion. Background technique [0002] Radar emitter signal modulation identification is an important link in electronic countermeasures and electronic reconnaissance, and plays a very important role in electronic warfare. In war, more information can be obtained to grasp the initiative. The complex electromagnetic military environment on the battlefield and the enhancement of the radar signal modulation technology system make the modulation and identification of radar emitter signals more and more difficult. For the ever-changing complex environment and radar signals, the existing recognition methods have low recognition effect, so it is urgent, necessary and meaningful to find new recognition methods. Radar signal modulation r...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to propose a recognition method, mainly to solve the problem of low recognition rate under the low signal-to-noise ratio of existing recognition methods

At the same time, using the pre-trained deep neural network to extract the internal details of the time-frequency image makes the feature extraction more comprehensive and effective, thus solving the problem of poor applicability of extracting fixed feature parameters

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