Abstract
Because the forming mechanism of underwater acoustic signal is complex, it is difficult to establish the accurate predicting model. In this paper, we propose a nonlinear predicting modeling method of ship radiated noise based on genetic algorithm. Three types of ship radiated noise are taken as real underwater acoustic signal. First of all, a basic model framework is chosen. Secondly, each possible model is done with genetic coding. Thirdly, model evaluation standard is established. Fourthly, the operation of genetic algorithm such as crossover, reproduction, and mutation is designed. Finally, a prediction model of real underwater acoustic signal is established by genetic algorithm. By calculating the root mean square error and signal error ratio of underwater acoustic signal predicting model, the satisfactory results are obtained. The results show that the proposed method can establish the accurate predicting model with high prediction accuracy and may play an important role in the further processing of underwater acoustic signal such as noise reduction and feature extraction and classification.
Highlights
Underwater acoustic signal processing is a major branch of signal processing
We propose a nonlinear predicting modeling method of ship radiated noise based on genetic algorithm
We employ recent developments on nonlinear physics and time series prediction to study the physical characteristics of measured underwater acoustic signal
Summary
Underwater acoustic signal processing is a major branch of signal processing. As road categories of underwater acoustic signal, ship radiated noise is generated by the nonlinearity of the marine environment and hull structure together, which contains a large amount of ship target’s position, distance, and depth information [1]. Modeling and prediction of underwater acoustic signal based on PSO and RBF neural network [6] are proposed Experimental results show this algorithm has better performance in terms of training accuracy and convergence rate and supports the modeling, prediction, and dynamic analysis of underwater acoustic signals. Prediction of underwater acoustic signals based on neural network [7] is proposed Predictions of both simulated data and real ship radiated noise data are made using BP and RBF network. Those prediction methods do not give an accurate mathematical expression of underwater acoustic signal. This paper tries to propose a predicting modeling method of ship radiated noise based on genetic algorithm
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