The paper analyzes the development of strapdown inertial airborne gravimeters, which have significant advantages over gyrostabilized gravimeters in terms of size, power consumption and cost and substantially expand the capabilities of gravimetric survey. Technical solutions are described that make implementation of strapdown airborne gravimeters possible. The trends in their development are discussed, including integration of data from strapdown and gyrostabilized gravimeters.

With the increase in accuracy and resolution of modern global models of the Earth’s gravity field, more opportunities have appeared to use them in solving the regional gravimetric problems. At the same time, the estimates of existing models depending on the region and geomorphology, as well as methods for predicting the reliability of data in models, taking into account the scale and nature of the problem being solved, become more important. The article is devoted to new estimates of modern models of the gravity field in various regions of the World Ocean and over various geomorphological structures. The estimates were obtained by comparing the data of the most relevant models of the gravity field with the data of high-precision marine areal and route surveys carried out in all major areas of the World Ocean. Based on the results, the model field is promising and it is possible to estimate the spatial distribution of model field errors in the World Ocean. A method for efficient preliminary zoning of a model field in the ocean is proposed. The features of the development of the Earth’s gravity field models are considered, taking into account their actual accuracy and resolution, as well as the issue of general reliability of modern model data in the high-latitude Arctic.

A method for calibration of strapdown inertial navigation systems (SINS) is proposed which combines the advantages of the approached based on the application of the Kalman filter, on the one hand, and estimates of changes in specific force in the horizon plane before and after rotation of the turntable, on the other. In contrast to the known methods of SINS calibration that take into account the changes in the horizon components of acceleration with a model measurement matrix in iterative calculations of corrections to biases, scale factors, and misalignments of accelerometers and gyroscopes (hereinafter called gyros), the approach described in this paper uses actual rotations and positions of the SINS with account for previous iterations rather than SINS uniaxial rotation angles and positions specified to a turntable.

The same experimental data were used to compare the proposed method with the one using the model measurement matrix. The results have shown that the overall error of the SINS calibrated by the proposed method is less than in the other case; in addition, the number of required iterative refinements is less. The proposed method allows navigation-grade SINS to be calibrated on low-accuracy turntables, with proper consideration for the inaccuracy of the SINS inertial measurement unit (IMU) rotation in shock absorbers.

The paper discusses the problem of a spacecraft attitude estimation and its solution by integrating the measurement data from an information-redundant gyro device and a stellar navigation system. The traditional solution methods are based on the use of Kalman filter of n+3 order, where n > 3 is the number of measurement channels (gyroscopes or angular rate sensors). The numerical implementation of the corresponding algorithm on an onboard computer requires significant computational efforts. To considerably reduce the computational complexity of the algorithm without losing the accuracy, it is proposed to use a method of decomposing the filter of n+3 order into three filters of the second order and n–3 filters of the first order.

The article analyzes the works devoted to outdoor navigation of unmanned aerial vehicles (UAVs) in GNSS-denied environments using computer vision systems (optical range cameras). The algorithms addressed are based on matching of UAV-generated images with the available georeferenced terrain images. Images are matched either pixel by pixel, by their key points, or using neural networks. The stages of each algorithm, as well as the accuracy achieved by the authors and the field data used for testing are considered. The paper concludes with a discussion of the capabilities and limitations of the proposed approaches.

Autonomous bottom sensor networks are increasingly used to collect various data near the sea bottom. Transmitting these large accumulated data arrays to the data collection and processing center is a pressing problem. A promising method to retrieve data from sensor nodes is to use multiple autonomous underwater vehicles (AUV). The quality of underwater mission performance is then determined by accurate navigation of each vehicle within the group. The article presents a new efficient method of multiple AUV navigation for performing the vital task – servicing the autonomous network of bottom sensor stations. The method requires neither beacons of long baseline acoustic navigation system (LBL ANS) nor surface vehicles. During the mission, some AUVs are moving to the target sensor nodes, while the others are docked to the sensor nodes, read out the accumulated data, and perform the maintenance procedures (battery recharging, state diagnostics, and correction of the mission program). The main idea of the method is that the AUVs docked to the sensor nodes function as temporary stationary beacons of the differential ranging (DR) ANS for the other moving AUVs. The algorithms of the proposed navigation method are considered.

The proposed real-time algorithm for autonomous underwater vehicle (AUV) relative position and attitude determination uses range measurements to acoustic beacons positioned at small distances to each other on a common platform. Mutual arrangement of AUV and beacons is a priori unknown, and their time scales are not synchronized. The developed algorithm considers the nonlinear character of measurements while featuring a lower computational burden compared to the maximum likelihood method. Results from simulation and postprocessing of real data with different AUV arrangement relative to the beacons are provided.

The article experimentally proves the importance of applying Differential Code Biases (DCB) when determining coordinates by Precise Point Positioning (PPP) based on multiGNSS measurements (GPS, GLONASS, Galileo). The application of DCB significantly reduces the convergence time of the navigation solution. Modifications to RTKLIB software required for the experiment are described, which allow applying the DCB in real time.

In challenging environments like urban vehicle navigation and geological hazards, the GNSS signals are easily blocked, and the long re-convergence time seriously limits many applications of real-time dynamic precise point positioning. Considering that the velocity accuracy is better than the position during re-convergence epochs, we proposed a real-time rapid-positioning method by introducing velocity constraints into the dynamic PPP. According to the different motion states and environments, different velocity constraints are used adaptively. For example, the zero-velocity constraint model is used in the stationary state; the Doppler-velocity constraint model is used when the most visible satellites are temporarily blocked; the other-sensors-velocity constraint model is used when the satellite signal is blocked frequently. Considering that the inaccurate dynamic model will affect the dynamic positioning results, the velocity constraint can be gradually relaxed after the GNSS signals are reacquired and the ambiguity gradually converges. Based on static and kinematic experiments with GPS data, the results show that when the number of visible satellites is greatly dropped due to signal blocking, the new positioning method can significantly speed up the re-convergence of precise point positioning, maintain high accuracy and improve the continuity of real-time dynamic positioning in a short time.

With the addition of multi-frequency and multi-constellation systems, the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) algorithm is expected to provide a global vertical and horizontal guidance for the localizer performance of vertical guidance (LPV)-200 approach phase in aeronautical navigation worldwide. Currently, the second and third generations of the BeiDou navigation satellite system (BDS-2 and BDS-3) provide their services to users. We consider ARAIM for dual-frequency iono-free BDS pseudorange combinations. With the aim to improve the service performance of the BDS-2 and BDS-3 systems, the assumed integrity support message (ISM) was used to calculate the vertical protection level (VPL) for the LPV-200 approach. The impact of the different parameters of ISM on the ARAIM availability was evaluated. The results demonstrate that, compared with BDS-3, the global coverage of availability for BDS-2+BDS-3 is slightly higher, mainly due to the increase of the number of visible satellites. The availability of BeiDou in the Americas is affected by user range accuracy (URA). With URA decreasing from 2.0 to 0.5 m, the ARAIM availability of BDS-2+BDS-3 in the Americas increased from 50 to 99.9%.

Light source is one of the key components of fiber optic gyroscopes. The performance of these gyros, including their scale factor and bias stability depend directly on the parameters of the light source output. Although the modern market offers a variety of light sources potentially suitable for fiber optic gyros, it seems quite challenging to choose a proper light source. The objective of this paper is to study and compare the light sources made by various companies, in particular, to measure and analyze the pattern and width of their spectra, weighted average wavelength, the output optical power, and the power consumption. A comprehensive comparative analysis of the obtained characteristics of the sources has been carried out.