Multi-Objectivization-Based Localization of Underwater Sensors Using Magnetometers

Underwater sensor networks are necessary to detect and track unknown targets in the maritime environment. Localization of sensors becomes a crucial problem. This paper presents a new method based on multi-objectivization to localize the sensors using triaxial magnetometers. In this localization system, a DC current-carrying solenoid coil serves as a magnetic source and the inertial magnetometer measure the three-component of magnetic flux intensity. Then, the localization problem is translated into a multi-objective optimization problem by minimizing each error function. Without using depth sensor, it is difficult to find the global optimum of the functions due to the homogeneous magnetic field. Accordingly, we propose a hybrid algorithm using improved non-dominated sorting genetic algorithm and linear multi-metering method to determine the sensor position. To reduce time consumption during the optimization process, a simplified discrete model of the magnetic field is derived. Experiment results show that the proposed localization method has a high accuracy and strong robustness.