Research on interference elimination of multi ship communication signals based on radial basis functions
Research on a method for eliminating signal interference in multi ship communication based on radial basis functions,to solve the problem of signal interference between multiple ships and the impact on communication quality.Set up shore base stations and ships in the ocean as transmitters and receivers,respectively.Consider the direct radiation,sea sur-face reflection,and atmospheric pipeline refraction paths during multi ship communication,construct a channel model for multi ship communication,and determine the characteristic parameters of multi ship communication signals.Using the ob-tained feature parameters as inputs to the radial basis function neural network,the clustering algorithm is employed to de-termine the center of the hidden layer nodes and the width of the radial basis function.Introducing forgetting factor and us-ing gradient learning method to train radial basis function neural network,adjusting the number and weights of hidden layer neurons.Utilize the trained radial basis function neural network to suppress signal interference in inter ship communication.The experimental results show that this method can effectively eliminate the interference components in multi ship commu-nication signals under static and dynamic interference,and reduce the signal transmission error rate.
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