The Navigation Algorithm of the Underwater Vehicle with Strapdown Inertial Navigation System

Navigation instruments


Vavilova N. B.*, Parusnikov N. A., Subkhankulova G. A.**

Lomonosov Moscow State University, 1, Leninskie Gory, Moscow, 119991, Russia



In the article the navigation problem for an autonomous underwater vehicle (AUV) is under consideration. In AUV’s navigation the following sensors are usually used: transponders that measure the distance from the AUV to transponders in known locations, velocity sensor, depth sensor, gyroscopic course sensor. A peculiarity of this work consists in the usage of Strapdown Inertial Navigation System (SINS) of medium accuracy together with mentioned above sensors. AUV’s navigation problem is posed as SINS correction problem with aiding measurements. Principal possibilities of this approach are investigated on the basis of the analysis of covariance with experimental data.

AUV are used in a wide range of scientific and applied research of ocean, such as a marine geological research, a study of the seafloor, ecological research of water environment. The value of the data provided by the underwater vehicle depends on the accuracy of a navigation system used. That is why the development of high-precision AUV’s navigation system is relevant today.

The presented paper differs from previous investigation in this domain by taking SINS of medium accuracy into consideration. Furthermore, data provided by SINS is regarded as the main data. Resulting navigation solution is based on SINS integration with aiding measurements delivered by special sonar beacon with known location (by means of GPS), sensors of velocity and depth. The estimation algorithm is based on technique of Kalman filtering. Mathematical models take into account specific peculiarities of AUV motion (low speed, relatively short distance between a vehicle and a beacon). The two typical types of the AUV’s motion were taken into account. The research method was based on analysis of covariance analysis with implementation of real data.

The experimental data was provided by scientific educational center «Underwater robotics», Far Eastern Federal University and IPMT RAS. Marine Autonomous Robotic System «MARK» has two main hardware parts — an autonomous underwater vehicle and an afloat vehicle. An equipment of a shore control center is also included. The afloat vehicle is a mobile beacon with a transponder. The location of the latter is determined by GPS. Vehicles have radio links with hydroacoustic communication system.

The presented article studies two representative mechanical trajectories of MARK’s motion. In the first case AUV moves rectilinearly with the constant depth, an afloat vehicle moves along a «zigzag» path with the side 200 m, intersecting the AUV’s trajectory. In the second case AUV moves along a square path clockwise with the side 100 m, an afloat vehicle moves along a square path counterclockwise with the side 200 m. In both cases the direction on the beacon was being changed and as a result the problem of position’s estimation became well-conditioned.

Derived results show that the standard deviations of the position’s estimation errors are less than 3 m.

The results of the preliminary analysis that was done give evidence the proposed algorithm can improve the accuracy of aided AUV’s navigation system in several times.


strapdown inertial navigation system, calibration, high-precision turntable


  1. Kropotov A.N., Makashov A.A., Plyasunov V.M. Trudy MAI, 2015, no. 80:

  2. Malyshev V.V., Kabanov D.S. Trudy MAI, 2012, no. 57:

  3. Golovan A.A., Parusnikov N.A. Matematicheskie osnovy navigatsionnykh sistem. Chast’ I. Matematicheskie modeli inertsial’noi navigatsii (Mathematical Foundations of navigation systems. Part I. Applications optimal estimation methods to the problems of navigation), Moscow, MAKS Press, 2012, 170 p.

  4. Golovan A.A., Parusnikov N.A. Matematicheskie osnovy navigatsionnykh sistem. Chast’ II. Prilozheniya metodov optimal’nogo otsenivaniya k zadacham navigatsii. (Mathematical Foundations of navigation systems. Part II. Mathematical models of inertial navigation), Moscow, MAKS Press, 2011, 132 p.

  5. Ageev M.D. Avtonomnye podvodnye roboty: sistemy i tekhnologii Avtonomnye podvodnye roboty: sistemy i tekhnologii (Autonomous underwater vehicles: systems and technologies), Moscow, Nauka, 2005, 398 p.

  6. Vaulin Yu.V., Dubrovin F.S., Kushernik A.A., Tufanov I.E., Shcherbatyuk A.F. Mekhatronika, avtomatizatsiya, upravlenie, 2012, no.6, pp. 59-65.

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