Practical Moving Target Detection in Maritime Environments Using Fuzzy Multi-sensor Data Fusion

As autonomous ships become the future trend for maritime transportation, it is of importance to develop intelligent autonomous navigation systems to ensure the navigation safety of ships. Among the three core components (sensing, planning and control modules) of the system, an accurate detection of target ships’ navigation information is critical. Within a typical maritime environment, the existence of sensor noises as well as the influences generated by varying environment conditions largely limit the reliability of using a single sensor for environment awareness. It is therefore vital to use multiple sensors together with a multi-sensor data fusion technology to improve the detection performance. In this paper, a fuzzy logic-based multi-sensor data fusion algorithm for moving target ships detection has been proposed and designed using both AIS and radar information. A two-stage fuzzy logic association method has been particularly developed and integrated with Kalman filtering to achieve a computationally efficient performance. The effectiveness of the proposed algorithm has been tested and validated in simulations where multiple target ships are transiting with complex movements

Adaptive Localisation for Unmanned Surface Vehicles Using IMU-Interacting Multiple Model

Unscented Kalman Filter (UKF) remains to be a prevalent multi-sensor fusion method in many practices, including navigational tracking for Unmanned Surface Vehicles (USVs). This paper suggests that results from UKF fusion is unsatisfactory for USVs’ relatively smooth path due to UKF’s lack of versatility. Hence, it is proposed here that by replacing the UKF with Interacting Multiple Model (IMM), estimation results will better represent USV’s movement. Furthermore, this paper proposes slight modification to the IMM in order to heighten the algorithm’s confidence in switching modes. By exploiting angular velocity information from Inertial Measurement Unit (IMU), an independent mode probability can be obtained which is then injected into the IMM. Computer simulations based on maritime operations were done to show that the proposed IMU-based IMM is able to react faster to mode changes, giving more reliable outcomes

A lattice Boltzmann method for axisymmetric thermocapillary flows

In this work, we develop a two-phase lattice Boltzmann method (LBM) to simulate axisymmetric thermocapil- lary flows. This method simulates the immiscible axisymmetric two-phase flow by an improved color-gradient model, in which the single-phase collision, perturbation and recoloring operators are all presented with the axisymmetric effect taken into account in a simple and computational consistent manner. An additional lattice Boltzmann equation is introduced to describe the evolution of the axisymmetric temperature field, which is coupled to the hydrodynamic equations through an equation of state. This method is first validated by simulations of Rayleigh-B ́enard convection in a vertical cylinder and thermocapillary migration of a de- formable droplet at various Marangoni numbers. It is then used to simulate the thermocapillary migration of two spherical droplets in a constant applied temperature gradient along their line of centers, and the influence of the Marangoni number (Ca), initial distance between droplets (S0), and the radius ratio of the leading to trailing droplets (Λ) on the migration process is systematically studied. As Ma increases, the thermal wake behind the leading droplet strengthens, resulting in the transition of the droplet migration from coalescence to non-coalescence; and also, the final distance between droplets increases with Ma for the non-coalescence cases. The variation of S0 does not change the final state of the droplets although it has a direct impact on the migration process. In contrast, Λ can significantly influence the migration process of both droplets and their final state: at low Ma, decreasing Λ favors the coalescence of both droplets; at high Ma, the two droplets do not coalesce eventually but migrate with the same velocity for the small values of Λ, and decreasing Λ leads to a shorter equilibrium time and a faster migration velocity

A hybrid lattice Boltzmann and finite difference method for two-phase flows with soluble surfactants

A hybrid method is developed to simulate two-phase flows with soluble surfactants. In this method, the interface and bulk surfactant concentration equations of diffuse-interface form, which include source terms to consider surfactant adsorption and desorption dynamics, are solved in the entire fluid domain by the finite difference method, while two-phase flows are solved by a lattice Boltzmann color-gradient model, which can accurately simulate binary fluids with unequal densities. The flow and interface surfactant concentration fields are coupled by a modified Langmuir equation of state, which allows for surfactant concentration beyond critical micelle concentration. The capability and accuracy of the hybrid method are first validated by simulating three numerical examples, including the adsorption of bulk surfactants onto the interface of a stationary droplet, the droplet migration in a constant surfactant gradient, and the deformation of a surfactant-laden droplet in a simple shear flow, in which the numerical results are compared with theoretical solutions and available literature data. Then, the hybrid method is applied to simulate the buoyancy-driven bubble rise in a surfactant solution, in which the influence of surfactants is identified for varying wall confinement, Eotvos number and Biot number. It is found that surfactants exhibit a retardation effect on the bubble rise due to the Marangoni stress that resists interface motion, and the retardation effect weakens as the Eotvos or Biot number increases. We further show that the weakened retardation effect at higher Biot numbers is attributed to a decreased non-uniform effect of surfactants at the interface