The paper discusses the data fusion of SINS accelerometers and gyroscopes and an odometer. The solution is based on three-dimensional (3D) inertial and 3D kinematic odometer dead-reckoning and continuous SINS updates by the computed 3D odometer coordinates. Important factors for the integration accuracy are highlighted: misalignments between the SINS instrument frame and the body frame; linear displacements of the SINS center relative to the odometer reference point; odometer scale factor error, and possible timing skews between raw SINS and odometer data. These parameters are included in the estimated variables in the data fusion algorithms. We demonstrate the necessity and efficiency of the proposed algorithmic solutions with experimental data analysis.
The study and analysis of the problem of simulation modeling of multipath radio channels based on the use of systems of differential equations is carried out. Mathematical models of continuous communication channels, presented in the form of stochastic differential equations, as well as approaches to their practical application in creating physical channel simulators and developing algorithms for optimal signal reception, are considered. Particular attention is paid to non-Gaussian models described by nonlinear stochastic differential equations. Methods of analysis of such models, their construction on the basis of initial data on probabilistic characteristics of signals and interference, as well as identification procedures performed on the results of measurements on real communication lines are considered in detail. In addition to theoretical aspects, engineering issues related to the implementation of channel simulators functioning according to the specified principles are also covered.
Modern geodetic monitoring methods require high accuracy and efficiency in detecting deformations of engineering structures. This article examines the application of terrestrial laser scanning (TLS) for determining the planar displacements of objects, with a primary focus on an experimental study of the method’s accuracy. The research is based on experimental data obtained from deformation modeling and the analysis of sequential observation cycles using point clouds. The aim of the study is to assess the capabilities of the TLS method in detecting small displacements and to determine its accuracy characteristics. The paper presents the methodology for processing point clouds and the algorithms for data analysis. Experiments have been conducted to demonstrate the method’s ability to detect displacements with high precision. The study identifies the limitations of TLS caused by the technical specifics of the equipment and proposes possible ways to minimize them. The results confirm the potential of TLS for high-precision structural monitoring, particularly in densely built environments where traditional methods may be less effective. The practical significance of this study lies in the possibility of integrating the proposed method into deformation monitoring systems for engineering structures such as buildings, bridges, and industrial constructions, thereby improving the reliability of geodetic measurements and enabling rapid response to critical structural changes.
The author examines some theoretical and methodological foundations of cartographic supporting scientific and technical activities. It is considered as a systemic process aimed at understanding aspects of the surrounding reality and making research and economic-management decisions using digital cartographic and geoinformation products. Interrelations and differences between cartographic support, mapping, geoinformation and other types of modeling are presented. The systems approach assumes existing of internal components, whose interrelations implement cognitive and communicative aspects of supporting. Taking into account the domestic experience, a conceptual model of the system’s structure is proposed. Basic components are represented by the result, methods and concepts, data sources, technical means and personnel. Interrelations of the components determine implementing the said process, forming properties of its outcome and improving its internal parts. The fundamental role of the identified elements in development of its functions was empirically confirmed. The advantages of the new methodological principle of cartographic support are described in detail. The proposed conceptual model allows maintaining the demand for mapping methods and specialists in implementation of scientific and technical tasks in the era of digital transformation of the society
Accurate monitoring natural and flooded water body areas is critical for natural resource management and disaster emergency response. Extracting water bodies over complex geographical scenes often struggles to balance spatial integrity and local detail accuracy, leading to problems like fragmentation, boundary loss, and omission of various water bodies, thereby reducing the reliability of the results. We propose the novel SWENet, a feature-collaborative convolutional neural network that utilizes transformer-assisted feature extraction under a multi-feature strategy. The framework synergistically strengthens linear and planar features of water bodies through edge, spectral, and texture features. A Transformer branch is introduced to capture supplementary contextual information, while a Bidirectional Gated Feature Fusion Module (BGFM) facilitates cross-feature interaction. A redesigned ASPP module fuses multi-scale features more effectively to strengthen the perception of global and local information. Comparative evaluations on SWF and FAS datasets demonstrate SWENet's performance against six leading SOTA segmentation models, with module-level functionality ablation experiments further verified via the XT dataset. The results indicate that SWENet can achieve outstanding efficiency in fragmented small water bodies and those affected by flood inundation in large-scale geographical context, demonstrating its comprehensive capabilities in various water body extraction tasks. This study can provide technical support for the monitoring of natural and flood-affected water bodies in areas with variable and complex hydrological conditions.
