The objective of this paper is to estimate performance of a new approach for spectrum sharing and coordination between terrestrial base stations (BS) and On-board radio access nodes (UxNB) carried by Unmanned Aerial Vehicles (UAV). This approach employs an artificial intelligence (AI) based algorithm implemented in a centralized controller. According to the assessment based on the latest specifications of 3rd Generation Partnership Project (3GPP) the newly defined Unmanned Aerial System Traffic Management (UTM) is feasible to implement and utilize an algorithm for dynamic and efficient distribution of available radio resources between all radio nodes involved in process of optimization. An example of proprietary algorithm has been described, which is based on the principles of Kohonen neural networks. The algorithm has been used in simulation scenario to illustrate the performance of the novel approach of centralized radio channels allocation between terrestrial BSs and UxNBs deployed in 3GPP-defined rural macro (RMa) environment. Simulation results indicate that at least 85% of simulated downlink (DL) transmissions are gaining additional channel bandwidth if presented algorithm is used for spectrum distribution between terrestrial BSs and UxNBs instead of baseline soft frequency re-use (SFR) approach.

The advance of MEMS-based inertial sensors successfully expands their applications to small unmanned

aerial vehicles (UAV), thus resulting in the challenge of reliable and accurate in-flight alignment for airborne

MEMS-based inertial navigation system (INS). In order to strengthen the rapid response capability

for UAVs, this paper proposes a robust in-flight alignment scheme for airborne MEMS-INS aided by global

navigation satellite system (GNSS). Aggravated by noisy MEMS sensors and complicated flight dynamics,

a rotation-vector-based attitude determination method is devised to tackle the in-flight coarse alignment

problem, and the technique of innovation-based robust Kalman filtering is used to handle the adverse impacts

of measurement outliers in GNSS solutions. The results of flight test have indicated that the proposed

alignment approach can accomplish accurate and reliable in-flight alignment in cases of measurement outliers,

which has a significant performance improvement compared with its traditional counterparts.

The Land and Property Register (LPR) also called the Cadastre by the legislator should function in accordance with regulations in force, meet expectations of the public and provide universal access to Register data for its users. Beyond any doubt, credibility and usefulness of data in this public register are affected by the manner it is kept, which generally in-cludes active and passive approach. If the LPR is kept in an active manner and constantly up to date, its data is very useful. The qualitative aspect of the land and buildings database’s records establishes the calculation accuracy of the owners’ land parcels evidenced in the Land and Mortgage Registers, which protect the ownership right to the property. In order to ensure that the plot of land is unequivocally and correctly measured, it is necessary to establish breakpoints of the parcels’ bounda-ries in the presence of the interested parties.

Research conducted on the possibility of using the unmanned aerial vehicle (UAV) for measuring purposes indicates immense probability where this technology may be used for the selected details of group I (most accurately located) in modernization of land and buildings registers.

One of the little described problems in hydrostatic drives is the fast changing runs in the hydraulic line of this drive affecting the nature of the formation and intensity of pressure pulsation and flow rate occurring in the drive. Pressure pulsation and flow rate are the cause of unstable operation of servos, delays in the control system and other harmful phenomena. The article presents a flow model in a hydrostatic drive line based on fluid continuity equations (mass conservation), maintaining the amount of Navier-Stokes motion in the direction of flow (x axis), energy conservation (liquid state). The movement of liquids in a hydrostatic line is described by partial differential equations of the hyperbolic type, so modeling takes into account the wave phenomena occurring in the line. The hydrostatic line was treated as a cross with two inputs and two outputs, characterized by a specific transmittance matrix. The product approximation was used to solve the wave equations. An example of the use of general equations is presented for the analysis of a miniaturized hydrostatic drive line fed from a constant pressure source and terminated by a servo mechanism.

The investigation of a decentralized radio network dedicated to unmanned aerial systems (UASs) was presented in the paper. Two frequencies (315 MHz; 434 MHz) and five different configurations of Gaussian frequency-shift keying (GFSK) were taken into account. Three different algorithms for decentralized networks were investigated and their influence on the network capacity was measured. The research was done both for static and dynamically changed unmanned aerial vehicle (UAV) positions. In order to quantify the research three different parameters were determined: RSSI, nP (number of data packets in one second), and f (frequency of data update).

This paper describes a synthetic aperture radar system for tactical-level imagery intelligence installed on board an unmanned aerial vehicle. Selected results of its tests are provided. The system contains interchange-able S-band and Ku-band linear frequency-modulated, continuous wave radar sensors that were built within a frame of a research project named WATSAR, conducted by the Military University of Technology and WB Electronics S.A. One of several algorithms of radar image synthesis, implemented in the scope of the project, is described in this paper. The WATSAR system can create online and off-line radar images.

The paper presents a method of calculation of position deviations from a theoretical, nominally rectilinear trajectory for a SAR imaging system installed on board of UAV. The UAV on-board system consists of a radar sensor, an antenna system, a SAR processor and a navigation system. The main task of the navigation part is to determine the vector of differences between the theoretical and the measured trajectories of UAV center of gravity. The paper includes chosen results of experiments obtained during ground and flight tests.

Understanding the factors that influence the quality of unmanned aerial vehicle (UAV)-based products is

a scientifically ongoing and relevant topic. Our research focused on the impact of the interior orientation

parameters (IOPs) on the positional accuracy of points in a calibration field, identified and measured in an

orthophoto and a point cloud. We established a calibration field consisting of 20 materialized points and

10 detailed points measured with high accuracy. Surveying missions with a fixed-wing UAV were carried

out in three series. Several image blocks that differed in flight direction (along, across), flight altitude

(70 m, 120 m), and IOPs (known or unknown values in the image-block adjustment) were composed. The

analysis of the various scenarios indicated that fixed IOPs, computed from a good geometric composition,

can especially improve vertical accuracy in comparison with self-calibration; an image block composed

from two perpendicular flight directions can yield better results than an image block composed from a single

flight direction.

The paper presents methods of on-line and off-line estimation of UAV position on the basis of measurements from its integrated navigation system. The navigation system installed on board UAV contains an INS and a GNSS receiver. The UAV position, as well as its velocity and orientation are estimated with the use of smoothing algorithms. For off-line estimation, a fixed-interval smoothing algorithm has been applied. On-line estimation has been accomplished with the use of a fixed-lag smoothing algorithm. The paper includes chosen results of simulations demonstrating improvements of accuracy of UAV position estimation with the use of smoothing algorithms in comparison with the use of a Kalman filter.

The aim of this research is to evaluate the performance of four UAV image processing software for the automatic estimation of volumes based on estimated volume accuracy, spatial accuracy, and execution time, with and without Ground Control Points (GCPs). A total of 52 images of a building were captured using a DJI Mavic Air UAV at 60m altitude and 80% forward and side overlap. The dataset was processed with and without GCPs using Pix4DMapper, Agisoft Metashape Pro, Reality Capture, and 3DF Zephyr. The UAV-based estimated volume generated from the software was compared with the true volume of the building generated from its as-built 3D building information modeled in Revit 2018 environment. The resulting percentage difference was computed. The average volumes estimated from the four software with the use of GCPs were 4757.448 m3 (3.87%), 4728.1 m3 (2.54%), 4291.561 m3 (11.5%), and 4154.938 m3 (14.35%), respectively. Similarly, when GCPs were not used for the image processing, average volumes of 4631.385 m3 (4.52%), 4773.025 m3 (1.6%), 4617.899 m3 (4.89%), and 4420.403 m3 (8.92%) were obtained in the same order. In addition to the volume estimation analysis, other parameters, including execution time, positional RMSE, and spatial resolution, were evaluated. Based on these parameters, Agisoft Metashape Pro proved to be more accurate, time-efficient, and reliable for volumetric estimations from UAV images compared to the other investigated software. The findings of this study can guide decision-making in selecting the appropriate software for UAV-based volume estimation in different applications.

The use of unmanned aerial vehicles (UAVs) is booming in almost every sector of the economy, especially in the agricultural industry. According to some reports, the agricultural UAV market is expected to increase from USD 2.6 billion in 2020 to USD 9.5 billion in 2030. In this paper a brief overview devoted to the use of UAVs in the Russian State Agrarian University – Moscow Timiryazev Agricultural Academy (RSAU-MTAA), including the results of studying the equipment use effectiveness for automatic driving of tractor equipment when sowing grain crops and planting potatoes. In the course of studying the equipment use effectiveness for automatic driving of tractor equipment, the deviations of the guess row spacing from the standard row spacing provided for by the seeder design were established; in the case of sowing barley using a marker, it was up to 4.3 cm, and in the case of winter wheat it was up to 5 cm. When using the autopilot system, these values were no more than 1.5 and 2.3 cm, respectively, which indicates the high accuracy and efficiency of the automatic driving systems. The autopilot system use provided a deviation of adjacent rows from the straightness when planting potatoes from 2.8 to 3.0 cm. The paper concludes that the use of unmanned robotic systems in agriculture, in conjunction with modern means of receiving and processing information, opens up new opportunities for increasing agriculture efficiency.

Geospatial data obtained using Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs) are increasingly used to model the terrain in the coastal zone, in particular in shallow waterbodies (with a depth of up to 1 m). In order to generate a terrain relief, it is important to choose a method for modelling that will allow it to be accurately projected. Therefore, the aim of this article is to present a method for accuracy assessment of topo-bathymetric surface models based on geospatial data recorded by UAV and USV vehicles. Bathymetric and photogrammetric measurements were carried out on the waterbody adjacent to the public beach in Gdynia (Poland) in 2022 using a DJI Phantom 4 RTK UAV and an AutoDron USV. The geospatial data integration process was performed in the Surfer software. As a result, Digital Terrain Models (DTMs) in the coastal zone were developed using the following terrain modelling methods: Inverse Distance to a Power (IDP), Inverse Distance Weighted (IDW), kriging, the Modified Shepard’s Method (MSM) and Natural Neighbour Interpolation (NNI). The conducted study does not clearly indicate any of the methods, as the selection of the method is also affected by the visualization of the generated model. However, having compared the accuracy measures of the charts and models obtained, it was concluded that for this type of data, the kriging (linear model) method was the best. Very good results were also obtained for the NNI method. The lowest value of the Root Mean Square Error (RMSE) (0.030 m) and the lowest value of the Mean Absolute Error (MAE) (0.011 m) were noted for the GRID model interpolated with the kriging (linear model) method. Moreover, the NNI and kriging (linear model) methods obtained the highest coefficient of determination value (0.999). The NNI method has the lowest value of the R68 measure (0.009 m), while the lowest value of the R95 measure (0.033 m) was noted for the kriging (linear model) method.

A navigation complex of an unmanned flight vehicle of small class is considered. Increasing the accuracy of navigation definitions is done with the help of a nonlinear Kalman filter in the implementation of the algorithm on board an aircraft in the face of severe limitations on the performance of the special calculator. The accuracy of the assessment depends on the available reliable information on the model of the process under study, which has a high degree of uncertainty. To carry out high-precision correction of the navigation complex, an adaptive non-linear Kalman filter with parametric identification was developed. The model of errors of the inertial navigation system is considered in the navigation complex, which is used in the algorithmic support. The procedure for identifying the parameters of a non-linear model represented by the SDC method in a scalar form is used. The developed adaptive non-linear Kalman filter is compact and easy to implement on board an aircraft.

Post-mining dumps are a common sight in the industrial areas of Silesia (Poland). Despite several reclamation projects, many of them still constitute an unresolved problem. It is not only a matter of unaesthetic view – they often pose a threat to the environment and the people living nearby. Despite revitalization, some dumps are not properly maintained and are at the risk of slope failure. Such places require constant geodetic observation and stability control. In this article, the example of a dump located in the city of Gliwice was used to show the possibilities offered by the use of photogrammetry and unmanned aerial vehicles (UAV) for cyclic checks of the embankment condition. The current state of the dump and the results of interventions after two incidents of slope failure,were observed. The main slopes of the terrain surface and at the selected cross-sections were determined in two flight missions. The obtained geometrical data were used in the further numerical analysis. Finite Element Method model representing one of the escarpment cross-sectionswas built to estimate the factor of safety and determine the main mechanisms responsible for the failure. Elastic-perfectly plastic Coulomb-Mohr model was used to describe the behaviour of the minestone and the ‘ c – tan φ reduction’ – for calculation of the stability. The problem of reliable material properties’ estimation was emphasized. The analysis included the impact of seepage and total head difference on the slope stability. It was concluded that the rainfall intensity had a decisive influence on the instability of the dump.

Extremely intensive development of technology has resulted in many innovations. There are new methods of acquiring spatial data, such as laser scanning, unmanned aerial vehicles or digital non-metric cameras, which are the subject of this study. Integration of this data has become a new tool that has expanded existing measurement capabilities, finding applications in 3D modelling, archaeology and monument conservation. Owing to scanning, we can get the coordinates of almost every point of the scanned surface, obtaining full and detailed information about the object dimensions. The level of technical advancement of digital cameras allows them to be successfully used in short-range photogrammetry [27], and recently also in low-altitude aerial photogrammetry (unmanned aerial vehicles). Two different test objects were selected to achieve the intended purpose. The monument located on the 14-meter-high top of the Wanda Mound was adopted as the first object. It consists of a simple rectangular plinth made of brown marble. On its top there is a figure of an eagle with a crown of white marble. On the west wall of the plinth there is an inscription “Wanda” and a drawing showing a sword crossed with a distaff. The following features supported the choice of the monument: interesting shape of the object, which includes both simple geometric forms with large and flat surfaces (plinth), and more detailed surfaces (figure of an eagle); detailed texture of the object (complicated marble veins, wing details). The second object under study was The Helena Modrzejewska National Stary Theatre. The building was rebuilt in the style of Viennese Art Nouveau, so that it fully incorporates into the rest of buildings. Measurements included data obtained from a non-metric camera, Leica ScanStation scanner and DJI S 1000 multi-rotor.

In a smart city environment, Intelligent Transportation System (ITS) enables the vehicle to generate and communicate messages for safety applications. There exists a challenge where the integrity of the message needs to be verified before passing it on to other vehicles. There should be a provision to motivate the honest vehicles who are reporting the true event messages. To achieve this, traffic regulations and event detections can be linked with blockchain technology. Any vehicle violating traffic rules will be issued with a penalty by executing the smart contract. In case any accident occurs, the vehicle nearby to the spot can immediately send the event message to Unmanned Aerial Vehicle (UAV). It will check for its credibility and proceed with rewards. The authenticity of the vehicle inside the smart city area is verified by registering itself with UAVs deployed near the city entrance. This is enabled to reduce the participation of unauthorized vehicles inside the city zone. The Secure Hash Algorithm (SHA256) and Elliptic Curve Digital Signature Algorithm (ECDSA-192) are used for communication. The result of computation time for certificate generation and vehicles involvement rate is presented.