НАВИГАЦИОННАЯ СИСТЕМА АВТОНОМНОГО ПОДВОДНОГО АППАРАТА НА ОСНОВЕ ДАННЫХ, ПЕРЕДАВАЕМЫХ ПО АКУСТИЧЕСКОМУ КАНАЛУ ОТ ГИДРОАКУСТИЧЕСКОЙ СТАНЦИИ

Abstract

The paper proposes a method for constructing a navigation system of an autonomous underwatervehicle (AUV) using a limited set of onboard sensors and receiving position data of the AUVvia 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 determinedusing its onboard sensors. Linear velocities are not directly measured. The Kalman filter isused to implement the navigation algorithm. At the same time, the feature of this algorithm is theimplementation of a two-stage procedure for correcting estimates of coordinates and linear velocitiesof 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 thecorrection of these estimates only on the basis of data from the depth sensor, which is updated ateach step of the system. And the second option is used when data comes from HUMS via acousticcommunication channels. This data comes with a delay due to the limited speed of propagation ofacoustic 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 previouslycalculated data and evaluating the necessary corrections by comparing the received data with theestimates obtained earlier. The proposed scheme for the construction of the navigation system allowsfor the correction of its readings in the conditions of irregular data updates from the HUMS. Theresults of modeling using a model describing all the main features of the HUMS operation and itsinteraction with the AUV (delays in obtaining information, the presence of measurement noise andsampling of HUMS data) showed a sufficiently high efficiency of the proposed solution. At the sametime, the main advantage can be indicated by the possibility of using a minimum number of on-boardsensors and the possibility of fast deployment of HUMS for interaction with AUV.