Considering the problem of invalid data caused mismatch of wavenumber spectrum which contained in turbulence observation data, an algorithm of turbulent wavenumber spectrum matching based on SVM is proposed. Category labels are obtained from pre-processed raw data by cross validation algorithm, and then the optimum parameters of the classifier are got through SVM learning algorithm. Sea trial data validation results indicate that the algorithm has high matching accuracy, and provides a new way to calculate the turbulence wavenumber spectrum matching.

Pressure hull is an important part of an underwater glider, on which the study was designed to ensure that it has sufficient strength and stability, the smallest weight, as well as the maximum internal deployment of space and load capacity. In order to find the best initial design solution of the pressure hull, this paper analyzes the design process of underwater vehicle systematically. After the shape and material selection of the main body and end cover, structural analysis and size optimization of pressure shell for autonomous underwater glider carried out by the finite element analysis tool Ansys Workbench, and the simulation results paves the way for the pressure test verification.

Considering the problem that vibration signals which are generated by three-axis accelerations will impact turbulence signal, an improved motion compensation algorithm based on discriminant analysis is proposed. The characteristics of three axis acceleration signals are got by using cross validation discriminant analysis method to test the performance of de-noising among different filtering orders which are got by three-axis accelerations vibration signals. Finally the discriminant function is found to get the optimal filter order. The results of simulation and real sea experiment data statistical analysis shows that the algorithm improves the de-noising performance and can be better applied to ocean turbulence signal de-noising processing.