International Journal of Computer Science Issues

More than a traditional journal...

Due to collect and monitor exploration of natural location resources which was difficult to acquire the location without Global Position System (GPS) in the underwater. However, there are something research was used Inertial Navigation System (INS) to location, but the INS accuracy degrades over time that the issue will be occurred, like as have uncompensated rate gyro, accelerometer errors, suffer from the drifts and biases and non-linear disturbances. This paper put forward a plan for improving the accuracy of position in INS. We devise an accuracy of position based on the Global Position System Inertial Navigation System (GINS), which the GINS derived filter is more accurate than Extended Kalman filter (EKF) for underwater sensor network. The GINS will get their position from GPS while floating above the water, and next step, they dive into water. In addition, we revised the location data from reference to oceanography profiles of fluid forces, which forces involved in underwater motion is included the buoyant force, the current force, and the fluid resistance force to correct the EKF error. And then the underwater of Cartesian coordinates (X, Y, Z) were an object with a predict-correct algorithm for solving the nonlinear dynamic systems at EKF. Finally, we present an adaptive GINS which can reduce costs of optimum position trade-offs in wide coverage of the location-based network.