The Self-organizing map (SOM) is an unsupervised neural network based on competitive learning, and can solve the problem that the center of clustering is unknown. SOM’s theory and the implementation of algorithm are studied in this paper. Simulating example is given to approve the feasibility of SOM in characteristic assessment for multivariate sample. The Ambient sea noise measurement is made in August 2014 on some sea of China. The total source level was forecasted using “ROSS formula” and the sailing information. The statistical variability of broadband ambient noise at frequencies between 20Hz and 31.5 kHz is obtained using SOM. The comparison between measured sound pressure and forecasting pressure is given, and the preliminary analysis of the relationship between ambient noise level and vessels is carried out. The results provide the technical reference to understand the temporal and spatial statistical variability of ambient noise, and are an efficient tool in assessing the potential effect of shipping noise on marine mammals in the special sea area.
Ship is a complex underwater volume source in shallow water; its raidated noise field has the spacial directivity, which results in an obvious difference of detecting pefrormance of passive sonar at different aspect angles. In this paper the multi-poles mathematical model of the ship radiated noise fiels is established in shallow water, and the method of detecting probability for ship is researched using passive sonar equation. The detected probalility is estimated at different aspect angles when the range between receiver and the source is given, at the same time the obtained results are compared. These simulated results are of particular importance for the safety of traveling ship in the sea.