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This paper studies a novel intelligent motion control algorithm for Autonomous Underwater Vehicles (AUV) and develops a virtual reality system for a new interactive experimental platform. The paper designs a robust neuro-fuzzy controller to tackle system uncertainties and external disturbances. Fuzzy control can solve the uncertainty problem of control systems. The neural network model self-tunes the controller parameters to improve the anti-interference ability. The designed control algorithm is verified using a MATLAB implementation and a virtual reality system. The virtual reality system developed in this paper can be used to debug the control algorithm, simulate the marine environment, and establish an ocean current interference model. The paper uses the MATLAB engine to realize the data communication between the MATLAB and the AUV virtual reality system. This allows the output order of the controller in MATLAB to drive the AUV in a virtual simulation system to simulate the 3D space motion.

A characteristic extraction algorithm of the ballistic missile hyperspectral data based on the quantization coding method is studied. The ballistic missile hyperspectral data of imaging spectrometer based on near-space platform is generated by numerical method. The characteristic of the ballistic missile hyperspectral data is extracted and matched using the characteristic extraction algorithm based on the quantization coding method. The simulation result show that the characteristic extraction algorithm is easy to implement and low complexity. The characteristic, which extracted by this algorithm, is enough to represent the speciality of the ballistic missile hyperspectral data. The matching algorithm has high accuracy.

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