فهرست مطالب hossien nourmohammadi

Since the Unmanned Underwater Vehicles (UUVs) don’t receive the Global Navigation Satellite System (GNSS) signals under the water, other aided measurements are needed to provide the required accuracy in tilt estimation including roll and pitch angle estimation. Conventional approaches for pressure-based tilt estimation, only consider the relation between the static pressure and the tilt as the measurement model. However, the performance of this approach depends on the dynamic pressure which is caused by the sea waves. This paper improves the accuracy of pressure-based tilt estimation using the more accurate of the measurement model. Also, the proposed approach considers the coupling between the axes of UUV. Due to the cost of the approach and the hardware limitations of installation pressure sensors, the proposed approach is implemented using two pressure sensors. An Extended Kalman Filter (EKF) is used for simultaneous tilt and gyroscopes measurement errors estimation. A Monte-Carlo simulation is developed to evaluate the performance of the proposed approach in comparison with INS only and the conventional static pressure-based tilt estimation. The simulation results show that tilt estimation performance of conventional approach is better than the INS only performance and the performance of proposed approach is better than the both of them.

Transfer alignment of master and slave systems plays a key role in the inertial navigation accuracy of the marine cooperative vehicles. Accuracy enhancement of misalignment angle and orientation estimation is the main purpose of the transfer alignment. Velocity and orientation matching is a well-known method for transfer alignment. However, in many applications, there are no velocity measurements of both the master and slave systems due to weight, dimensional and technological limitations of accurate speed sensors such as Doppler Velocity Loggers (DVL). Angular velocity configuration is a suitable solution for transfer alignment in this situation. But, the orientation error cannot be estimated in this configuration. Taking into account this drawback, a new configuration based on using the integral of angular velocity in addition to angular velocity measurement is presented for transfer alignment in the current research. Furthermore, appropriate abilities are considered to estimate the dynamic misalignment angle, orientation error and also measurement errors of the slave gyroscope. Two linear and non-linear observation models are developed for the transfer alignment configuration. The simulation results reveal the appropriate performance of the proposed configuration for marine application especially when there are no accurate velocity measurements. Based on the simulation results, the performance of the non-linear observation model is better than linear ones in dynamic misalignment angle estimation. Moreover, it can be inferred from the orientation error estimation that rich data in high-maneuvered motion is necessary for required estimation accuracy. Also, a 200 runs of Monte-Carlo simulation is developed and the estimation RMSE are presented.