The effect of constant delays in the information of inertial sensors on errors of the strapdown inertial navigation system is considered. This effect is especially noticeable for some movements that can be realized during bench tests or during operation. This allows to develop some test plans to detect and evaluate sensor delays.

The paper describes a method of airborne gravimetry using the Chekan-AM gravimeter. Specific details of measurements processing in the case of draped gravimetric survey are discussed, and the results of detailed airborne gravimetry survey are presented.

This article discusses the problem of estimating spacecraft trajectory parameters based on data provided by a GNSS (Global Navigation Satellite System) receiver and onboard spacecraft motion prediction algorithms. The traditional approach to solving the mentioned problem relies on Kalman filtering techniques for estimating the spacecraft’s coordinates and velocity. The navigation algorithms in the onboard computer must meet the technical requirements for maximum reduction in computational load. The paper proposes a method of decomposition for onboard integration algorithm using three parallel secondorder filters. This algorithmic approach significantly reduces the computational load of the algorithm, while maintaining accuracy. The main goal of this paper is to design a decomposed algorithm for estimation problem posed.

The uncertainty of the model parameters of integrated navigation system and the instability of the system model are characteristic of unstructured environment. For these systems, large estimation errors are likely to occur if a fixed single model is used for navigation solutions. To solve this problem, a Bayesian network enhanced interacting multiple model (BN-IMM) filtering algorithm is proposed. In the proposed algorithm, certain motion characteristic variables are introduced on the basis of multi-model estimation, and Bayesian networks are established according to the causal relationship between variables and the system model. Bayesian network parameters are used to modify the model switching probability in multi-model estimation, which can reduce the dependence of real model recognition on prior knowledge in multi-model algorithm. The proposed algorithm can solve the problems such as model conversion lag and model probability mutation in the interacting multi-model (IMM) algorithm, and enhance the adaptive ability of the multi-model algorithm. The proposed BN-IMM was utilized as a local sub-filter within a federated filter, establishing an information fusion algorithm architecture for the strapdown inertial navigation system (SINS)/global positioning system (GPS)/odometer integrated navigation system. In the test, the output of gyro and accelerometer was taken as characteristic variables to build a Bayesian network. The established Bayesian network was used to dynamically predict the uncertainties in the integrated navigation system. The actual road tests demonstrate that the proposed federated BN-IMM algorithm can significantly enhance the stability and accuracy of state estimation in the integrated navigation system.

In critical safety domains like civil aviation, Receiver Autonomous Integrity Monitoring (RAIM) supports integrity services from oceanic routes to non-precision approaches (NPA). The expansion of GNSS (Global Navigation Satellite System) civil frequencies improves these services. To evaluate RAIM availability enhancements from Multi-Frequency Multi-System (MFMS) integration, observation data and broadcast ephemeris from 18 global Multi-GNSS Experiment (MGEX) stations were analyzed for GPS/BDS/Galileo (Global Positioning System/BeiDou Navigation Satellite System/Galileo Navigation Satellite System) combinations. The results indicate that MFMS integration significantly improves positioning and integrity performance compared to single-system operation.

The article presents the results of testing the algorithm, considered in the first part, for determining the position of an autonomous underwater vehicle (AUV) based on measurements of ranges to acoustic beacons and on the data from a water-speed log and a heading indicator. Distinctive features of the algorithm are the start without using AUV a priori coordinates and without the set of measurements required for an unambiguous navigation solution, recursive processing, in the same filter, of current measurements and those saved before the algorithm starts, and accounting for the ambiguity of the AUV position and its resolution. The performance of the proposed algorithm is compared with other possible solutions. The results of simulation and field data post-processing have been obtained, which make it possible to estimate the time to get the first unambiguous solution and the accuracy of unambiguous solutions using the developed algorithm with a different number and location of acoustic beacons and the AUV trajectory. The cases are considered when the desynchronization of the beacon and AUV clocks is a random variable and when the desynchronization is unknown; consequently, either range measurements or range-difference measurements are used. The solutions are compared taking into account the measurements saved before the algorithm start and without taking them into account.

The paper describes the design of an algorithm for three-dimensional radio tomography of electron concentration in the ionosphere based on the GNSS data. Simulation data are used to describe the algebraic reconstruction techniques underlying the algorithm design; also considered are the methods taking into account a priori information as well as the approaches to optimization of parameters of these algebraic methods. The results of the experimental ionospheric reconstruction obtained with the use of the data obtained from the satellite system of precise positioning of the Republic of Belarus are presented.

A method is proposed for position, navigation and timing (PNT) support based on instant measurements of parameters of signals from the global navigation satellite system GLONASS and quasars in radio interferometric systems with ultra-long baseline formed by relocatable small-sized radio telescopes (SRT) whose location is to be updated. This composition of signal sources and the possibility to relocate the SRT to form the radio interferometer’s baseline increase the PNT process stability. The proposed approach relies upon the radio interferometry used for precision positioning of a user according to the measured coordinates and the PNT time reference, with simultaneous coordinate referencing of the base telescope. It is assumed that in the radio interferometer formed in this manner, both positions do not have precision coordinate references, and the time scale of one of the telescopes, formed by the local standard, needs to be matched and updated regularly. This method can be useful when providing the PNT support to special users whose location has no essential infrastructure.

The article proposes new approaches to estimating the error of navigation devices in the dynamic mode, which is a stationary process. These approaches are based on generating pseudo-random oscillations in a given frequency spectrum in accordance with the operating conditions on board a ship. The approaches are adapted for use on available testing equipment and make it possible to simplify the experimental error estimation when monitoring the performance of serial products. Testing was carried out in laboratory conditions with estimating the errors of an electronic inclinometer and a magnetic compass in the dynamic mode. The results of these experiments are consistent with those obtained earlier during field research. The error of the electronic inclinometer was also estimated in the dynamic mode using a deterministic approach – when generating harmonic oscillations with a known frequency and amplitude. It is shown that the error obtained with the deterministic approach does not fully display the real error of the devices under their operating conditions.
The proposed methods allow us to reduce the time for estimating the error of sensors and systems from several hours to 15-20 minutes, because they do not require separate measurements at each frequency. These methods also allow obtaining additional information on the components of the device error. It is concluded that when assessing the error of devices in the dynamic mode on a test bench, it is advisable to generate an input signal corresponding to specific operating conditions.