Methods of improving the coordinates determining accuracy using inertial geodetic systems

The authors consider the principle of geodetic definitions using inertial systems in the absence of signals from satellite radio navigation systems and insufficient density of the initial geodetic base. A technique of improving the coordinates’ accuracy determining using inertial geodetic systems is proposed. Compensation of these systems’ errors is performed through joint equalization of data received from the inertial system, gyrotheodolite and rangefinder. In order to test the methodology, a mathematical model of the ground object movement with an inertial geodetic system was compiled. The simulation results confirm the suitability of the developed methodology. A full-scale experiment was conducted to test the efficiency of the technique. Its results are consistent with those of the simulation. The analysis of the data obtained enables concluding that the developed technique provides an increase in the accuracy of determining coordinates using inertial geodetic systems in the absence or distortion of signals from satellite radio navigation systems and insufficient density of the initial geodetic base. That is why it can be used in operational geodetic training under conditions of autonomy.

Compensation Gyrocompass Based on MEMS

The study of an astatic compensating gyrocompass, built on the basis of a modulation micromechanical gyroscope (MMG) of a hybrid type, has been carried out. A kinematic diagram is given and the principle of operation of the device has describing. The device uses the modulation principle based on obtaining information about the angular motion of the rotor and creating control torques in a rotating coordinate system, which makes it possible to exclude such a significant disadvantage of MMG as "zero offset". A feature of the gyrocompass under consideration is the use of two channels for controlling the rotor of the MMG, namely: a channel for the formation of a guiding moment, striving to combine its main axis with the direction of the true meridian and a channel for compensating this guiding moment. A linearized mathematical model has building, on the base of which an effective algorithm for the operation of a compensatory astatic gyrocompass is proposed. The device under consideration can be used to determine the true azimuth of the longitudinal axis of a mobile ground object, it has a higher measurement speed compared to devices built on three-degree "heavy" gyroscopes, and has good resistance to external influences (vibrations, shocks, etc.).

The Method of Operational Planning of Group Actions of Aircraft in the "Air Taxi" Mode

The article is devoted to the development of algorithms for operational planning of routes for a group of aircraft (AC). We consider group actions of small and unmanned aircraft in the "air taxi" mode, when there is no regular flight schedule between the points of destination, and requests are received "on call" for flights to points whose composition is unknown in advance and is of a random nature. The multicriteria task of planning a group flight in the "air taxi" mode is being solved. The solution to this problem is proposed using the apparatus of the queuing theory, according to which the system under consideration belongs to the class of multichannel queuing systems with waiting. A method for solving the problem of operational planning of aircraft actions is proposed. An algorithm for group target distribution of new claims between aircraft is developed on the basis of a modified minimax criterion for assigning the nearest aircraft for an object with a maximum service time. The developed algorithm is based on the following four main operations: in the first operation, priority unserved targets are selected according to the criterion of assigning a dynamic priority; in the second operation, the formed list is ranked according to another criterion, taking into account the importance and total distance of each ground object from the aircraft group, in three this operation selects the object with the maximum rank, and for it the task of assigning "own" aircraft is solved according to the third criterion of maximum proximity, in the fourth operation the conditions of non-intersection of the group flight routes are checked. A computer model of the system for servicing requests in the air taxi mode has been developed. The developed model makes it possible to analyze various scheduling algorithms, as well as to determine at each step the number of free claims and the number of free and busy aircraft. A comparison is made between the well-known in the theory of queuing and the proposed minimax approaches. It is shown that, in comparison with the known variants of scheduling in the queuing theory, on the basis of the proposed approach, the optimal number of used aircraft is achieved.

Contribution Degree of Different Surface Factors in Urban Interior to Urban Thermal Environment

The contribution degree of different surface factors (complexity and heterogeneity) in the urban interior to the urban thermal environment has become an issue of increasing concern under changing climate. In this paper, the multiple linear regression analysis methods to analyze the contribution degree of different surface factors to the urban thermal environment were based on seven urban built-up areas. At the same time, the LST of the same type of factors in the same city will have a difference of ±2.5°C due to the different surrounding features. At the same time, the LST of the same ground object in the same city will be ±2.5°C different because of the difference of the surrounding ground object. The environmental LST and the mean LST of other surface factors were significantly correlated, and the root mean square error was 3.52. This study first classifies the ground features with different attributes, conducts LST statistics for each category, and conducts multivariate linear analysis, instead of setting some fuzzy exponent and forcing a threshold to calculate. The purpose is to explore the contribution of different reflectivity ground objects to the urban thermal environment.

Monocular Vision Ranging and Camera Focal Length Calibration

The camera calibration in monocular vision represents the relationship between the pixels’ units which is obtained from a camera and the object in the real world. As an essential procedure, camera calibration calculates the three-dimensional geometric information from the captured two-dimensional images. Therefore, a modified camera calibration method based on polynomial regression is proposed to simplify. In this method, a parameter vector is obtained by pixel coordinates of obstacles and corresponding distance values using polynomial regression. The set of parameter’s vectors can measure the distance between the camera and the ground object in the field of vision under the camera’s posture and position. The experimental results show that the lowest accuracy of this focal length calibration method for measurement is 97.09%, and the average accuracy was 99.02%.

Spectral-Spatial Hyperspectral Image Semisupervised Classification by Fusing Maximum Noise Fraction and Adaptive Random Multigraphs

Hyperspectral images (HSIs) contain large amounts of spectral and spatial information, and this provides the possibility for ground object classification. However, when using the traditional method, achieving a satisfactory classification result is difficult because of the insufficient labeling of samples in the training set. In addition, parameter adjustment during HSI classification is time-consuming. This paper proposes a novel fusion method based on the maximum noise fraction (MNF) and adaptive random multigraphs for HSI classification. Considering the overall spectrum of the object and the correlation of adjacent bands, the MNF was utilized to reduce the spectral dimension. Next, a multiscale local binary pattern (LBP) analysis was performed on the MNF dimension-reduced data to extract the spatial features of different scales. The obtained multiscale spatial features were then stacked with the MNF dimension-reduced spectral features to form multiscale spectral-spatial features (SSFs), which were sent into the RMG for HSI classification. Optimal performance was obtained by fusion. For all three real datasets, our method achieved competitive results with only 10 training samples. More importantly, the classification parameters corresponding to different hyperspectral data can be automatically optimized using our method.