NAVIGATION SYSTEM OF AN AUTONOMOUS UNDERWATER VEHICLE BASED ON DATA TRANSMITTED VIA AN ACOUSTIC CHANNEL FROM A HYDROACOUSTIC STATION

Abstract

The paper proposes a method for constructing a navigation system of an autonomous underwater vehicle (AUV) using a limited set of onboard sensors and receiving position data of the AUV via acoustic communication channels from a hydroacoustic underwater monitoring station (HUMS). The proposed method obtains estimates of the position and velocities of the AUV based on its dynamic model, assuming that the angular velocities, orientation angles and depth of the AUV are determined using its onboard sensors. Linear velocities are not directly measured. The Kalman filter is used to implement the navigation algorithm. At the same time, the feature of this algorithm is the implementation of a two-stage procedure for correcting estimates of coordinates and linear velocities of the AUV obtained on the basis of its dynamic model. This correction is carried out in two ways, depending on what data is available at the current step of the system. The first option assumes the correction of these estimates only on the basis of data from the depth sensor, which is updated at each step of the system. And the second option is used when data comes from HUMS via acoustic communication channels. This data comes with a delay due to the limited speed of propagation of acoustic signals in the aquatic environment, and may also periodically be distorted and disappear. The paper proposes a method for compensating for these delays by saving an array of previously calculated data and evaluating the necessary corrections by comparing the received data with the estimates obtained earlier. The proposed scheme for the construction of the navigation system allows for the correction of its readings in the conditions of irregular data updates from the HUMS. The results of modeling using a model describing all the main features of the HUMS operation and its interaction with the AUV (delays in obtaining information, the presence of measurement noise and sampling of HUMS data) showed a sufficiently high efficiency of the proposed solution. At the same time, the main advantage can be indicated by the possibility of using a minimum number of on-board sensors and the possibility of fast deployment of HUMS for interaction with AUV.