A Time-Domain Numerical Simulation for Free Motion Responses of Two Ships Advancing in Head Waves

The constant panel method within the framework of potential flow theory in the time domain is developed for solving the hydrodynamic interactions between two parallel ships with forward speed.When solving problems within a time domain framework,the free water surface needs to simultaneously satisfy both the kinematic and dynamic boundary conditions of the free water surface.This provides conditions for adding artificial damping layers.Using the Runge−Kutta method to solve equations related to time.An upwind differential scheme is used in the present method to deal with the convection terms on the free surface to prevent waves upstream.Through the comparison with the available experimental data and other numerical methods,the present method is proved to have good mesh convergence,and satisfactory results can be obtained.The constant panel method is applied to calculate the hydrodynamic interaction responses of two parallel ships advancing in head waves.Numerical simulations are conducted on the effects of forward speed,different longitudinal and lateral distances on the motion response of two modified Wigley ships in head waves.Then further investigations are conducted on the effects of different ship types on the motion response.

Combining Self-Organizing Map and Lipschitz Condition for Estimation in Direction of Arrival

There are many DOA estimation methods based on different signal features, and these methods are often evaluated by experimental results, but lack the necessary theoretical basis. Therefore, a direction of arrival (DOA) estimation system based on self-organizing map (SOM) and designed for arbitrarily distributed sensor array is proposed. The essential principle of this method is that the map from distance difference of arrival (DDOA) to DOA is Lipschitz continuity, it indicates the similar topology between them, and thus Kohonen SOM is a suitable network to classify DOA through DDOA. The simulation results show that the DOA estimation errors are less than 1° for most signals between 0° to 180°. Compared to MUSIC, Root-MUSIC, ESPRIT, and RBF, the errors of signals under signal-to-noise ratios (SNR) declines from 20 dB to 2 dB are robust, SOM is better than RBF and almost close to MUSIC. Further, the network can be trained in advance, which makes it possible to be implemented in real-time.

Entropy-based multipath detection model for MIMO radar

An optimized detection model based on weighted entropy for multiple input multiple output (MIMO) radar in multipath environment is presented. After defining the multipath distance difference (MDD), the multipath received signal model with four paths is built systematically. Both the variance and correlation coefficient of multipath scattering coefficient with MDD are analyzed, which indicates that the multipath variable can decrease the detection performance by reducing the echo power. By making use of the likelihood ratio test (LRT), a new method based on weighted entropy is introduced to use the positive multipath echo power and suppress the negative echo power, which results in better performance. Simulation results show that, compared with non-multipath environment or other recently developed methods, the proposed method can achieve detection performance improvement with the increase of sensors.

New optimal algorithm of data association for multi-passive-sensor location system

In dense target and false detection scenario of four time difference of arrival （TDOA） for multi-passive-sensor location system, the global optimal data association algorithm has to be adopted. In view of the heavy calculation burden of the traditional optimal assignment algorithm, this paper proposes a new global optimal assignment algorithm and a 2-stage association algorithm based on a statistic test. Compared with the traditional optimal algorithm, the new optimal algorithm avoids the complicated operations for finding the target position before we calculate association cost; hence, much of the procedure time is saved. In the 2-stage association algorithm, a large number of false location points are eliminated from candidate associations in advance. Therefore, the operation is further decreased, and the correct data association probability is improved in varying degrees. Both the complexity analyses and simulation results can verify the effectiveness of the new algorithms.