Research on Interference Suppression and Adaptive Adjustment Methods for Navigation and Communication Systems Based on Machine Learning
In order to achieve the goals of high integration,miniaturization,light weight and low power consumption,this paper studies a method of interference suppression and adaptive adjustment of navigation communication system based on machine learning.By summarizing the basic theories of navigation communication system,including signal modulation technology and spread spectrum technology,the possible natural and man-made interference in the system is analyzed in detail,and the importance of Signal Noise Ratio(SNR)and Bit Error Rate(BER)in system performance evaluation is emphasized.In order to improve the system performance,machine learning technology is introduced to verify the application potential of supervised learning and unsupervised learning in navigation and communication systems.At the same time,an interference suppression method based on machine learning is proposed,and its effectiveness is verified by experiments.In the simulation experiment,after applying this algorithm,the SNR is improved and the BER is reduced,which proves that the proposed algorithm is effective and provides new ideas and technical support for the optimal design of navigation communication systems in the future.
machine learningnavigation communication systeminterference suppressionadaptive adjustment
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