Communication signal modulation identification method of quantum elephant population mechanism evolution BP neural network

Abstract

The invention provides a communication signal modulation identification method of a quantum elephant population mechanism evolution BP neural network. A weighted Myriad filter is designed in combination with a data set of designed characteristic parameters, and then the BP neural network is evolved by using the quantum elephant population mechanism to obtain optimal system parameters of the neuralnetwork. And the BP neural network with the optimal weight and threshold is used as a classifier to efficiently identify the communication signal modulation mode under an impact noise background. Thedesigned method can acquire optimal network parameters and classification and recognition effects in an impact noise environment, so that a relatively high recognition rate is obtained in severe environments like impact noise and a low mixed signal-to-noise ratio, and the application limit of existing neural network modulation and recognition is broken through.

Description

technical field [0001] The invention relates to a communication signal modulation mode recognition method based on quantum phase group mechanism evolution BP neural network under impact noise, and belongs to the field of communication signal processing. Background technique [0002] Modulation identification technology is a very key technology in the field of wireless communication. Identifying the modulation mode of wireless communication signals is the basic technology in the fields of electronic countermeasures, electronic reconnaissance, non-cooperative communication, smart antennas, and wireless spectrum management. This technology is used in military Or civilian field all has very extensive application and very important value. In recent years, with the rapid development of wireless communication technology, electronic technology and signal processing and other technologies, the modulation methods of wireless communication signals have become more and more complex, and...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the problem that the performance of the existing communication signal modulation recognition method deteriorates seriously or even fails in the environment of impact noise or strong shock noise, and it is difficult to determine the optimal parameters of the BP neural network used as a modulation recognition classifier. The weighted Myriad filter combines the data set of the designed characteristic parameters, and then uses the quantum elephant swarm mechanism to evolve the BP neural network, obtains the optimal system parameters of the neural network, and uses the BP neural network with the optimal weight and threshold as the classifier pair Efficient identification of communication signal modulation modes in the background of impact noise

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