Three-dimensional scene interpretation through information fusion

1991 ◽  
Author(s):  
Sylvia S. Shen
Keyword(s):  
Information Fusion ◽  
Three Dimensional ◽  
Scene Interpretation

Terrain Matching Positioning Method Based on Node Multi-information Fusion

2016 ◽  
Vol 70 (1) ◽  
pp. 82-100 ◽  
Author(s):  
Ye Li ◽  
Rupeng Wang ◽  
Pengyun Chen ◽  
Peng Shen ◽  
Yanqing Jiang
Keyword(s):  
Information Fusion ◽  
Bottom Topography ◽  
Three Dimensional ◽  
Position Information ◽  
Surface Information ◽  
Positioning Method ◽  
Dimensional Distribution ◽  
Measured Information ◽  
Terrain Matching ◽  
Terrain Features

Measurement bias and lack of terrain features often cause false peaks during underwater terrain matching positioning, that is, there is more than one peak near the real position. Previous methods to address this problem have increased the number of measurement beams, but this also increases the data processing time and energy consumption. At the same time, the ratio of measured information that is used does not increase. In other words, we should increase the ratio of measured information that is used, not simply increase the amount of information that is measured. Conventional matching algorithms only use the height of nodes without considering surface information, which is composed of height and the position of multiple nodes in three-dimensional space. Multi-beam sonar can obtain the three-dimensional distribution of terrain nodes. This node information is not just a height sequence, as it is used in previous methods. If we consider the nodes as a three-dimensional distribution of points with height and position information, this increases the matching position information and more of the terrain features can be extracted from the same measured data. Hence, in this paper, a terrain positioning method called the Node Multi-information Fusion (NMIF) is presented. This method focuses on improving the stability and accuracy degraded by bias in the Digital Elevation Map (DEM), terrain repeatability, and other factors. First, the concept of a Single Node Data Packet (SNDP) is introduced. The SNDP includes elevation and surface information surrounding the node, such as roughness, gradient, and slope. This additional topographic feature information improves the robustness and accuracy of the system. A computer simulation using actual ocean bottom topography verifies the advantages of the proposed NMIF algorithm.

scholarly journals Coastal Ecological Environment Monitoring and Protection System Based on Multisource Information Fusion Decision

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Lijuan Xu ◽  
Lihong Zhang ◽  
Zhenhua Du
Keyword(s):  
Decision Making ◽  
Monitoring System ◽  
Marine Environment ◽  
Information Fusion ◽  
Three Dimensional ◽  
Data Access ◽  
Protection System ◽  
Monitoring Data ◽  
Ecological Environment ◽  
Environment Monitoring

With the problem of nuclear leakage being concerned by more and more industries, the research of coastal ecological environment monitoring has become more and more important. Therefore, it is necessary to study the current unsystematic coastal ecological environment monitoring and protection system. Aiming at the accuracy of feature fusion and representation of single short environment information, this paper compares the classification effects of the three fusion methods on four classifiers: logistic regression, SVM, random forest, and naive Bayes, to verify the effectiveness of LDA and DS model fusion and determine the consistency vector representation method of short environment information data. This paper collects and analyzes the coastal data in recent years using multisource information fusion decision-making. In this paper, DS (Dempster Shafer) evidence algorithm is used to collect the data of coastal salinization degree and air relative humidity, and then, the DS feature matching model is introduced to fuse the whole index system. The method in the article completes the standardized and standardized processing of monitoring data digital conversion, quality control, and data classification, forms interrelated four-dimensional spatiotemporal data, and establishes a distributed, object-oriented, Internet-oriented dynamic management real-time and delayed database. Finally, this paper carries out tree decision processing on the coastal ecological environment monitoring data of multisource information fusion, to achieve the extraction and intuitive analysis of special data, and puts forward targeted protection strategies for the coastal ecological environment according to the data results of the DS algorithm. The research shows that the number of indicators in multisource information fusion in this paper is 16, a total of 3251 data, 2866 meaningful information, and 1869 data including ecological cycle. These data are the results of the collection of multi-information data. Based on the multilevel nature of the existing marine environment three-dimensional monitoring system, the study established a comprehensive resource-guaranteed framework and divided it into four levels according to the level of the marine monitoring system: country, sea area, locality, and data access point. In specific analysis, the guarantee resources involved in each level are introduced. On the basis of in-depth analysis of the requirements of the marine environment three-dimensional monitoring system operation guarantee and the guarantee resource structure, the marine environment three-dimensional monitoring operation comprehensive guarantee system is described from the internal structure and the external connection. The DS algorithm extracts the status information resources of various marine environment three-dimensional monitoring systems, through the interaction of various subsystems, realizes the operation and maintenance of the monitoring system, and provides various technical supports such as system evaluation and failure analysis. After multisource information fusion and decision-making, it is obtained that the index equilibrium module in the DS algorithm in this paper is 0.52, the sensitivity is 0.68, and the independence is 0.42. Among them, the range of sensitivity is the largest. In the simulation results, the eco-economic coefficient can be increased from 12% to 36%. Therefore, using the method of multisource information fusion for quantitative index analysis can provide data support for coastal ecological environment detection, to establish a more perfect protection system.

Research of Three-Dimensional Layered Network Architecture LDM3 for ITS

2015 ◽  
Vol 719-720 ◽  
pp. 791-797
Author(s):  
Ya Duan Ruan ◽  
Xiang Jun Chen ◽  
Qi Mei Chen
Keyword(s):  
Information Fusion ◽  
Network Architecture ◽  
Intelligent Transportation System ◽  
Three Dimensional ◽  
Transport Layer ◽  
Massive Data ◽  
Local Dynamic ◽  
Application Layer ◽  
Application Systems ◽  
Dynamic Map

As Intelligent Transportation System (ITS) grows increasingly in size and complexity, the issues on how to improve interoperability and the performance of processing massive data become more critical. This paper proposes a new three-dimensional layered network architecture called Local Dynamic Map/Multimedia/Management (LDM3) to address these issues. In LDM3, the three-dimensional architecture consists of the information fusion layer newly introduced, as well as the application layer and transport layer. The primitive mechanism defined in the architecture improves the efficiency of the communication of network elements in such heterogeneous network system. By using the standardized format of message and data, the application systems can get desired information pushed by information fusion layer, instead of processing data from all kinds of sensors. This mechanism improves the effectiveness of the whole system significantly by avoiding duplicate work on different application systems. Meanwhile, the workload and the hardware requirement for application systems are relieved. We apply LDM3in the demonstration project for traffic Internet Of Things (IOT) in Jiangsu province. The result shows LDM3is an effective and efficient solution for ITS.

scholarly journals Pursuer Navigation Based on Proportional Navigation and Optimal Information Fusion

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Shulin Feng ◽  
Zhanxin Li ◽  
Li Liu ◽  
Hongyong Yang ◽  
Yuanhua Yang ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Information Fusion ◽  
Three Dimensional ◽  
Proportional Navigation ◽  
Kinematics Model ◽  
Application Range ◽  
Environment Simulation ◽  
Optimal Information ◽  
Point To Point ◽  
Proportional Navigation Law

Pursuer navigation is proposed based on the three-dimensional proportional navigation law, and this method presents a family of navigation laws resulting in a rich behavior for different parameters. Firstly, the kinematics model for the pursuer and the target is established. Secondly, the proportional navigation law is deduced through the kinematics model. Based on point-to-point navigation, obstacle avoidance is implemented by adjusting the control parameters, and the combination can enrich the application range of obstacle avoidance and guidance laws. Thirdly, information fusion weighted by diagonal matrices is used for decreasing the tracking precision. Finally, simulations are conducted in the MATLAB environment. Simulation results verify the availability of the proposed navigation law.

PGNet: Progressive Feature Guide Learning Network for Three-dimensional Shape Recognition

2021 ◽  
Vol 17 (3) ◽  
pp. 1-17
Author(s):  
Jie Nie ◽  
Zhi-Qiang Wei ◽  
Weizhi Nie ◽  
An-An Liu
Keyword(s):  
Deep Learning ◽  
Information Fusion ◽  
Visual Information ◽  
Feature Fusion ◽  
Shape Representation ◽  
Shape Recognition ◽  
Three Dimensional ◽  
Learning Network ◽  
3D Shape ◽  
Fusion Scheme

Three-dimensional (3D) shape recognition is a popular topic and has potential application value in the field of computer vision. With the recent proliferation of deep learning, various deep learning models have achieved state-of-the-art performance. Among them, multiview-based 3D shape representation has received increased attention in recent years, and related approaches have shown significant improvement in 3D shape recognition. However, these methods focus on feature learning based on the design of the network and ignore the correlation among views. In this article, we propose a novel progressive feature guide learning network (PGNet) that focuses on the correlation among multiple views and integrates multiple modalities for 3D shape recognition. In particular, we propose two information fusion schemes from visual and feature aspects. The visual fusion scheme focuses on the view level and employs the soft-attention model to define the weights of views for visual information fusion. The feature fusion scheme focuses on the feature dimension information and employs the quantified feature as the mask to further optimize the feature. These two schemes jointly construct a PGNet for 3D shape representation. The classic ModelNet40 and ShapeNetCore55 datasets are applied to demonstrate the performance of our approach. The corresponding experiment also demonstrates the superiority of our approach.

Three-dimensional target tracking strategy based on guidance laws and optimal information fusion

2020 ◽  
pp. 014233122096279
Author(s):  
Yihua Dong ◽  
Shulin Feng ◽  
Liuchen Tai
Keyword(s):  
Information Fusion ◽  
Control Strategy ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Proportional Navigation ◽  
Application Range ◽  
Optimal Information ◽  
Guidance Laws ◽  
Tracking Strategy ◽  
Three Dimensional Space

This paper presents a method for pursuer to track a moving target in a three-dimensional space. The method is based on the guidance laws combined with the kinematics equations of the pursuer and the target. The maneuvers of the target are prior unknown to the pursuer. Guidance laws used for tracking are the deviated pursuit and the proportional navigation, and the method presents a family of navigation laws resulting in a rich behavior for different parameters. For the three-dimensional scenario, two cases-not presenting interference and presenting interference are considered. In the absence of interference, the control strategy is proposed to implement the problem of tracking. In the presence of interference, an optimal information fusion Kalman filter weighted by scalars and guidance laws are combined to improve the trajectory tracking precision, and the combination can enrich the application range of information fusion and guidance laws. Simulations are conducted to demonstrate the effectiveness and reliability of the proposed control strategy.

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