Matching Area Selection Research Articles

A high-altitude geomagnetic matching area selection approach based on geomagnetic information entropy and geomagnetic direction entropy

Aiming at the obvious trend of the contours on the high-altitude geomagnetic map, this paper presents a method of high-altitude geomagnetic matching area selection combining geomagnetic information entropy and geomagnetic direction entropy based on the study of geomagnetic information entropy and geomagnetic direction entropy. The method first uses geomagnetic information entropy to select the region with rich geomagnetic information, and then determines the direction of the flight trajectory according to geomagnetic direction entropy to obtain the optimal matching trajectory. Finally, the method compares and analyzes the matching localization results of three flight trajectories in different directions on the geomagnetic map at an altitude of 30,000 m by using semi-physical simulation. The experimental results show that the flight navigation error along the trajectory with small information entropy is small, and its positioning error is 12.7% of the trajectory positioning error along the maximum information entropy direction. Selecting the flight trajectory according to the value of the geomagnetic direction entropy can greatly improve the precision and reliability of the geomagnetic matching localization. The method in this paper can provide a basis for path planning of the geomagnetic matching navigation.

Matching area selection for arctic gravity matching navigation based on adaptive all‐field extended extremum algorithm

AbstractSuitable and effective matching area selection is crucial for gravity matching‐aided navigation. In this paper, an all‐field extended extremum algorithm based on an adaptive threshold (AT‐AEE) is proposed for matching area selection in the Arctic Sea. The gradient data is obtained by using the convolution of gravity reference graph data and all‐field extended extremum parameters. Then, the adaptive threshold method was employed to determine the optimal gradient threshold based on gravity anomaly data across various test areas. Data points with gradients exceeding the specified threshold are identified as local candidate points for matching areas. The test areas containing a certain proportion of local candidate points are designated as the suitable matching areas. Nine test areas in the Arctic Sea with different gravity change characteristics were chosen for simulation experiments to verify the performance of the proposed algorithm. Simulation experiments showed that superior navigation positioning results could be obtained in the matching areas selected by the AT‐AEE algorithm. Compared to traditional algorithm, the matching areas derived from the AT‐AEE algorithm performed with a better consistency in the gravity matching navigation results. In suitable matching areas with the proportion of local candidate points reaching 70%, the average positioning errors could be reduced to less than 1.5 n miles.

The Underwater Gravity Matching Navigation Adaptation Area Is Preferred Based on The Multi-Starting Point TERCOM Algorithm

This paper focuses on the selection of matching area in gravity matching navigation system of underwater submersible. To solve the adaptation of the study region by using the TERCOM algorithm, this paper proposes the trajectory matching with three equal starting points within the study area. The experimental results show that this method can divide the adaptation area of the study area more comprehensively.

Wavelet Transform Based Morphological Matching Area Selection for Underwater Gravity Gradient-Aided Navigation

Selection of gravity gradient matching area is one of the key techniques for underwater gravity gradient-aided navigation. The existing matching area selection methods ignore the high-resolution characteristics of the gravity gradient, resulting in inaccurate selection. Therefore, a frequency domain matching area selection method based on the high-resolution characteristics of the gravity gradient is proposed. The high-frequency information of gravity gradient reference map is extracted by wavelet transform, and the gravity gradient wavelet transform model is established. The morphological image texture segmentation method is proposed to extract the densely textured areas from the gravity gradient high-frequency image as the matching areas. Simulation results show that the proposed method can obtain the texture density, texture amplitude and texture direction in the matching area while obtaining the matching area with a matching rate higher than 90%. Compared with the existing methods, the matching areas obtained by the proposed method are more accurate and the calculation burden is reduced to less than 10% of the existing algorithm. Moreover, the more the trajectory is perpendicular to the texture inside the matching area, the higher is the matching rate.

A Filtered-Marine Map-Based Matching Method for Gravity-Aided Navigation of Underwater Vehicles

Gravity-aided inertial navigation system (INS) has been widely applied in the application of autonomous underwater vehicle. Due to the uneven distribution of the gravitational field, the matching performance varies unsteadily when underwater vehicles pass through real marine environment. In this article, a filtered marine map-matching method based on sliding window iterated closest contour point (ICCP) algorithm is proposed. The filtered marine-map records the information of the contour line, which is extracted from the gravity anomaly value. The trajectory can be represented by different vectors between the contour lines corresponding to the sampled gravity points. In addition, a model-free matching area selection method is proposed. A multilayer support vector classifier is established by hierarchical classification method. The genetic algorithm is adopted to optimize the penalty factor and kernel function parameters. The marine experimental results indicate that the proposed matching area selection method can fully excavate the gravity information and provide directional guidance. The proposed filtered marine map-matching algorithm effectively improved the matching accuracy for underwater vehicles.

Optimal selection and adaptability analysis of matching area for terrain aided navigation

The existing terrain aided navigation (TAN) has the disadvantage that the navigation performance is limited by the size of matching area and terrain features. Therefore, this study proposes a method of optimal selection and adaptability analysis of matching area for TAN. According to the heading angle of the carrier, inertial navigation system positioning error and performance index, the optimal matching area is selected in real time. First, the matching area selection and adaptability analysis are carried out, and the influence of the matching area on the positioning performance is analysed by using the Beijing Internal TAN II algorithm. Then, the model parameters of the optimal matching area are determined through theoretical calculation and simulation. Finally, it is compared with the typical matching area selecting method. The test results show that the optimal selection and adaptability analysis method can improve the computational efficiency of TAN system, and improve the positioning accuracy of TAN system.

A co‐occurrence matrix‐based matching area selection algorithm for underwater gravity‐aided inertial navigation

The matching area selection algorithm is one of the key technologies for underwater gravity-aided inertial navigation system, which directly affects the positioning accuracy and matching rate of underwater navigation. The traditional matching area selection algorithms usually use the statistical characteristic parameters of gravity field. However, the traditional algorithms are difficult to reflect the spatial relation characteristic of gravity field, which always miss some latent matching areas with obvious change of gravity field. In order to solve this problem, the matching area selection algorithm based on co-occurrence matrix is proposed. The proposed algorithm establishes gravity anomaly co-occurrence matrix and extracts spatial relation characteristic parameters to reflect the gravity field. The comprehensive spatial characteristic parameter is built by entropy and is used to select the matching area by maximization of inter-class variance. The experimental results show that the proposed algorithm can select more effective matching areas than the traditional algorithms.

A Delaunay Triangulation-Based Matching Area Selection Algorithm for Underwater Gravity-Aided Inertial Navigation

The matching area selection algorithm is one of the key technologies for underwater gravity-aided inertial navigation system. Positioning accuracy and matching rate of gravity matching can be improved in high quality matching area. The traditional matching area selection algorithms usually use the statistical characteristic parameters of gravity field, which is difficult to reflect the spatial characteristics of gravity field. In order to explore more vector characteristics and spatial relation characteristics of gravity field and find more potential matching areas, the matching area selection algorithm based on Delaunay triangulation is proposed in this article. The proposed algorithm establishes the three-dimensional model and extracts spatial feature parameters to analysis gravity field. The comprehensive characteristics matrix is used to select matching area by feature extraction and cluster analysis. The experimental results show that the proposed algorithm can extract more characteristics of gravity field, and select more effective matching areas than the traditional algorithms.

CIRCULARITY: A Metric for Region Template Selection in Airborne Vision Navigation

Reliability template is a key factor of airborne vision navigation system. This paper proposes a new metric for region template selection. Firstly, a measurement model for uncertainty and inaccuracy of edge feature is given in detail. Furthermore, the influence of spatial distribution of edge features of correct recognition probability is analyzed in statistical probability theory. Then an “ideal” spatial distribution of region template which is the most easy to be recognized is proved by extreme-case analysis. Finally, a new metric is proposed by calculating the shape distance from this “ideal” spatial distribution, called CIRCULARITY, which can be deemed as “geometry self-similarity” to one target. The validity of new metric is experimentally demonstrated by using real ground targets. The results show that the new metric can meet the requirements of matching area selection and generating template.

Sum Vector-Difference-Based Matching Area Selection Method for Underwater Gravity-Aided Navigation

For underwater gravity matching navigation, matching area selection has a significant impact on navigation accuracy. Since the changes of gravity anomaly between grids of gravity background map is different, when the underwater vehicle passes through the same matching area in different directions, the matching efficiency is also different. Therefore, for measuring the navigability of each grid point, a gravity anomaly sum vector-difference parameter is proposed. Its direction is with the largest comprehensive difference of local gravity anomaly, which can estimate the local matching direction. Its modulus value is the absolute difference of the gravity anomaly value between the central point and its local region. Compared to traditional scalar parameter, the vector parameter can obtain the matching suitability of the direction. In order to select efficient matching areas, the entropy method is applied to fuse the proposed sum vector-difference parameter with traditional gravity characteristic parameters to obtain the comprehensive characteristic parameter. Simulation results show that compared with the traditional method, the proposed method fully used the gravity information, and selected matching areas are more concentrated and continuous.

Matching area selection of an underwater terrain navigation database with fuzzy multi-attribute decision making method

Selecting suitable underwater terrain navigation matching areas is a prerequisite for building an underwater terrain navigation database, which is important for vehicles operating underwater. By using information features to evaluate underwater terrain matching areas, vague sets are proposed to evaluate matching performance. Mathematical models of matching area features are built and topographic factor eigenvalues are obtained. With the topographic factor eigenvalues, fuzzy relationships between factor sets and judge sets are calculated. Vague set uses membership functions and non-membership functions to define the influence of topographic factor eigenvalues on matching suitability. Simulation results demonstrate that vague set theory can overcome the deficiency of single value in fuzzy sets and define the effect of geographic characteristics for matching performance. Based on vague set method, selection rules for terrain navigation matching areas in underwater terrain database are put forward.

The Gravity Matching Area Selection Criteria for Underwater Gravity-Aided Navigation Application Based on the Comprehensive Characteristic Parameter

Matching area selection is a key problem of the gravity matching navigation method, especially for underwater application. The gravitational profile varies when the vehicle gets into the matching area in different directions. Therefore, the matching navigation efficiency is also distinct due to the directionality of matching area. In this study, based on the fractal geometry theory, a characteristic parameter—isotropic coefficient, which can measure the directionality of gravity matching area–is proposed by analyzing the spectrum character of gravity anomaly sequence on 3-D surface. Instead of single parameter, the comprehensive characteristic parameter is built by combining traditional gravity parameters and isotropic coefficient through an analytic hierarchy process for matching area selection. Compared with the traditional method, simulation results prove that the matching area selected by the improved comprehensive characteristic parameter method not only has larger coverage, but also has better directivity.

Navigability analysis of magnetic map with projecting pursuit-based selection method by using firefly algorithm

The performance of geomagnetic aided navigation is closely related to the selection of geomagnetic matching area. This paper mainly studies the selection method of multi-parameter geomagnetic matching area based on the projection pursuit model, and then adopts the firefly algorithm, particle swarm optimization algorithm and differential evolution algorithm to obtain the optimal projection direction. After that, we compare the optimizing results comprehensively and give the evaluation of navigation performance in geomagnetic matching area to provide the basis for the selection of matching area. The implementation results show that when there are large differences between the characteristic parameters, the computation efficiency of firefly algorithm performs significantly better than the other two optimization algorithms. And under the same experimental conditions, the optimal geomagnetic matching area obtained by the method presented in this paper has the minimum matching position error and optimal navigation performance.

Control of Autonomous Mobile Robot Using Map Matching with Optimized Search Range

SUMMARYAccurate estimation of self‐position is indispensable for autonomous mobile robots. Map‐matching‐based self‐positioning is a promising method; however, adequate matching area selection is an issue to be solved. In this paper, we propose an adjustable map matching method that remedies a defect of the conventional template matching technology. The proposed method was evaluated experimentally, and the results confirmed the advantages of the proposed method.

Control of Autonomous Mobile Robot Using Map Matching with Optimized Search Range

SUMMARY Accurate estimation of self-position is indispensable for autonomous mobile robots. Map-matching-based self-positioning is a promising method; however, adequate matching area selection is an issue to be solved. In this paper, we propose an adjustable map matching method that remedies a defect of the conventional template matching technology. The proposed method was evaluated experimentally, and the results confirmed the advantages of the proposed method.

Research on Suitable Matching Area Selection Based on Wavelet Multi-scale Edge

Research on Suitable Matching Area Selection Based on Wavelet Multi-scale Edge