To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.

A novel variable step-size modified super-exponential iteration (MSEI) decision feedback blind equalization (DFE) algorithm with second-order digital phase-locked loop is put forward to improve the convergence performance of super-exponential iteration DFE algorithm. Based on the MSEI-DFE algorithm, it is first proposed to develop an error function as an improvement to the error function of MSEI, which effectively achieves faster convergence speed of the algorithm. Subsequently, a hyperbolic tangent function variable step-size algorithm is developed considering the high variation rate of the hyperbolic tangent function around zero, so as to further improve the convergence speed of the algorithm. In the end, a second-order digital phase-locked loop is introduced into the decision feedback equalizer to track and compensate for the phase rotation of equalizer input signals. For the multipath underwater acoustic channel with mixed phase and phase rotation, quadrature phase shift keying (QPSK) and 16 quadrature amplitude modulation (16QAM) modulated signals are used in the computer simulation of the algorithm in terms of convergence and carrier recovery performance. The results show that the proposed algorithm can considerably improve convergence speed and steady-state error, make effective compensation for phase rotation, and efficiently facilitate carrier recovery.