Errors of a strapdown inertial navigation system (INS) based on navigation grade fiber-optic gyros (FOG) are studied, with the INS measurement unit performing modulation rotation about the axis orthogonal to the vehicle deck. The main focus is made on the problem of reducing the time of gyro in-run drifts calibration, using the GNSS data when the INS is turned on. In addition to velocity and position measurements taken by the GNSS, phase measurements from antennas spaced on a certain baseline are included.

Information processing is carried out using extended Kalman filter; the data obtained during the bench tests of prototype FOG-based INS with a rotary measurement unit, and of GNSS compasses designed by CSRI Elektropribor, are used as well.

Two methods for construction and use of integrated inertial and satellite systems are considered, taking into account the specific features of aviation-related applications, namely, pre-flight alignment and autocalibration. Pre-flight alignment is performed during aircraft maneuvering on the aerodrome. Autocalibration of strapdown inertial navigation systems (SINS) is based on using the estimations of instrumental errors of inertial sensors, which had been obtained by the complex information processing (CIP) algorithm in a number of previous flights of the aircraft. The results of numerous flight tests of laser SINS designed by PAO MIEA for civil and military applications are provided as an evidence of high efficiency of the information integration methods proposed herein.

A Novel Adaptive Unscented Kalman Filter namely (NAUKF) has been developed and applied to fuse the outputs of strap-down IMU, the measurements of GPS satellites (pseudo-range and Doppler), strap-down magnetometer and a barometric altimeter, using tight coupling architecture. The proposed filter NAUKF considers the residual unmodeled noises of process and measurement as non-zero mean Gaussian white noises, estimates and compensates for the mean (bias) and covariance of the noise online, based on the principles of adaptive filtering, even if they are time-varying quantities. Employing the adaptive filtering principle into UKF, the nonlinearity of system can be restrained and the NAUKF is obtained. The noise statistic estimators designed in the proposed algorithm are built on basis of forgetting factors which are usually calculated empirically, in this research a new calculation concept based on “Genetic Algorithm” as an optimization tool is utilized to determine the optimal values of forgetting factors. The performance and convergence of noise statistic estimators used in NAUKF are checked by Monte-Carlo simulation. The utilization of NAUKF for Tightly-Coupled INS/GPS Integration (TCI) showed a superiority against the UKF for TCI especially during the GPS outages. The comparison is done experimentally by means of real flight trip of an UAV.

Findings from the study of gyroplatform control error effect on the accuracy of initial azimuth orientation of inclinometer are presented. A mathematical model of inclinometer gyroinertial module is developed and studied. A method for correcting the initial azimuth error induced by gyroplatform control error is proposed.

It has been demonstrated that inertial body flat shape changing under inertial loads results in gap variation in capacitance transducer of sense oscillations. Algorithm of moving electrode design parameters improvement is proposed to keep the device conversion efficiency insensitive to translational vibrations directed normally to the inertial body disc plane, taking into account the flat shape loss.

The paper presents the conceptual design of an integrated gravimetric system for measuring absolute gravity aboard vehicles. The mock-up system consisting of series-produced gravimeters GABL-PM and Chekan-AM is described along with its operating procedure. The mock-up system bench and field tests results are presented.

Comparative analysis of quality has been performed for the models of total electron content which could be applied in single-frequency navigation receivers of GPS/GLONASS. The analysis is based on the evaluation of total electron content modeling errors versus its experimentally measured values represented by global ionosphere maps (GIM). The GEMTEC model jointly developed by Irkutsk State University (IGU) and Irkutsk Branch of Moscow State Technical University of Civil Aviation (MGTU GA) has proven to show the least averaged errors.

In the course of creating Kalman filter it is inevitable that a continuous linear stochastic system must be transformed to its discrete equivalent. In this paper a new method for calculating covariance matrices in the discrete system is developed on the basis of Picard’s iterative process. Substantial calculating advantages of the proposed method compared to routine methods as applied to Kalman algorithm are shown.