scholarly journals Using the Decomposition-Based Multi-Objective Evolutionary Algorithm with Adaptive Neighborhood Sizes and Dynamic Constraint Strategies to Retrieve Atmospheric Ducts

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2230
Author(s):  
Yanbo Mai ◽  
Hanqing Shi ◽  
Qixiang Liao ◽  
Zheng Sheng ◽  
Shuai Zhao ◽  
...  
Keyword(s):  
Evolutionary Algorithm ◽  
Dynamic Change ◽  
Optimal Solution ◽  
Satellite System ◽  
Propagation Loss ◽  
Observation Data ◽  
Multi Objective ◽  
Adaptive Neighborhood ◽  
Global Navigation Satellite ◽  
Atmospheric Ducts

The traditional method of retrieving atmospheric ducts is to use the special sensor of weather balloons or rocket soundings to obtain information intelligently, and it is very expensive. Today, with the development of technology, it is very convenient to retrieve the atmospheric ducts from Global Navigation Satellite System (GNSS) phase delay and propagation loss observation data, and then the GNSS receiver on the ground forms an automatic receiving sensor. This paper proposes a hybrid decomposition-based multi-objective evolutionary algorithm with adaptive neighborhood sizes (EN-MOEA/ACD-NS), which dynamically imposes some constraints on the objectives. The decomposition-based multi-objective evolutionary algorithm (MOEA/D) updates the solutions through neighboring objectives, the number of which affects the quality of the optimal solution. Properly constraining the optimization objectives can effectively balance the diversity and convergence of the population. The experimental results from the Congress on Evolutionary Computation (CEC) 2009 on test instances with hypervolume (HV), inverted generational distance (IGD), and average Hausdorff distance ∆2 metrics show that the new method performs similarly to the evolutionary algorithm MOEA/ACD-NS, which considers only the dynamic change of the neighborhood sizes. The improved algorithm is applied to the practical problem of jointly retrieving atmospheric ducts with GNSS signals, and its performance further demonstrates its feasibility and practicability.

scholarly journals Online Near real-time Mine Disaster Monitoring System Based on Geosensor Networks

2016 ◽  
Vol 12 (03) ◽  
pp. 64
Author(s):  
Haifeng Hu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Satellite System ◽  
Open Pit ◽  
Observation Data ◽  
Complex Data ◽  
Disaster Monitoring ◽  
Process Observation ◽  
Global Navigation Satellite ◽  
Safety And Stability

Abstract—An online automatic disaster monitoring system can reduce or prevent geological mine disasters to protect life and property. Global Navigation Satellite System receivers and the GeoRobot are two kinds of in-situ geosensors widely used for monitoring ground movements near mines. A combined monitoring solution is presented that integrates the advantages of both. In addition, a geosensor network system to be used for geological mine disaster monitoring is described. A complete online automatic mine disaster monitoring system including data transmission, data management, and complex data analysis is outlined. This paper proposes a novel overall architecture for mine disaster monitoring. This architecture can seamlessly integrate sensors for long-term, remote, and near real-time monitoring. In the architecture, three layers are used to collect, manage and process observation data. To demonstrate the applicability of the method, a system encompassing this architecture has been deployed to monitor the safety and stability of a slope at an open-pit mine in Inner Mongolia.

A multi-objective evolutionary algorithm based on niche selection in solving irregular Pareto fronts

2021 ◽  
pp. 1-21
Author(s):  
Xin Li ◽  
Xiaoli Li ◽  
Kang Wang
Keyword(s):  
Evolutionary Algorithm ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Benchmark Problems ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Environmental Selection ◽  
Optimal Solution Set ◽  
Pareto Fronts

The key characteristic of multi-objective evolutionary algorithm is that it can find a good approximate multi-objective optimal solution set when solving multi-objective optimization problems(MOPs). However, most multi-objective evolutionary algorithms perform well on regular multi-objective optimization problems, but their performance on irregular fronts deteriorates. In order to remedy this issue, this paper studies the existing algorithms and proposes a multi-objective evolutionary based on niche selection to deal with irregular Pareto fronts. In this paper, the crowding degree is calculated by the niche method in the process of selecting parents when the non-dominated solutions converge to the first front, which improves the the quality of offspring solutions and which is beneficial to local search. In addition, niche selection is adopted into the process of environmental selection through considering the number and the location of the individuals in its niche radius, which improve the diversity of population. Finally, experimental results on 23 benchmark problems including MaF and IMOP show that the proposed algorithm exhibits better performance than the compared MOEAs.

Validation of the accuracy of geodetic automated measurement system based on GNSS platform for continuous monitoring of surface movements in post-mining areas

2021 ◽  
Vol 112 (1) ◽  
pp. 47-57
Author(s):  
Violetta Sokoła-Szewioła ◽  
Zbigniew Siejka
Keyword(s):  
Continuous Monitoring ◽  
Surface Deformation ◽  
Optimal Solution ◽  
Satellite System ◽  
Reference Points ◽  
Hard Coal ◽  
Navigation Systems ◽  
Mining Areas ◽  
Global Navigation ◽  
Global Navigation Satellite

Abstract The problem involving the monitoring of surface ground movements in post-mining areas is particularly important during the period of mine closures. During or after flooding of a mine, mechanical properties of the rock mass may be impaired, and this may trigger subsidence, surface landslides, uplift, sinkholes or seismic activity. It is, therefore, important to examine and select updating methods and plans for long-term monitoring of post-mining areas to mitigate seismic hazards or surface deformation during and after mine closure. The research assumed the implementation of continuous monitoring of surface movements using the Global Navigation Satellite System (GNSS) in the area of a closed hard coal mine ‘Kazimierz-Juliusz’, located in Poland. In order to ensure displacement measurement results with the accuracy of several millimetres, the accuracy of multi-GNSS observations carried out in real time as a combination of four global navigation systems, Global Positioning System (GPS), Globalnaja Navigacionnaja Sputnikova Sistema (GLONASS), Galileo and BeiDou, was determined. The article presents the results of empirical research conducted at four reference points. The test observations were made in variants comprising measurements based on: GPS, GPS and GLONASS systems, GPS, GLONASS and Galileo systems, GPS, GLONASS, Galileo and BeiDou systems. For each adopted solution, daily measurement sessions were performed using the RTK technique. The test results were subjected to accuracy analyses. Based on the obtained results, it was found that GNSS measurements should be carried out with the use of three navigation systems (GPS, GLONASS, Galileo), as an optimal solution for the needs of continuous geodetic monitoring in the area of the study.

scholarly journals A Joint Dual-Frequency GNSS/SINS Deep-Coupled Navigation System for Polar Navigation

2018 ◽  
Vol 8 (11) ◽  
pp. 2322 ◽  
Author(s):  
Lin Zhao ◽  
Mouyan Wu ◽  
Jicheng Ding ◽  
Yingyao Kang
Keyword(s):  
Navigation System ◽  
Density Ratio ◽  
Satellite System ◽  
The Arctic ◽  
Observation Data ◽  
Dual Frequency ◽  
Vector Tracking ◽  
Time Observation ◽  
Global Navigation Satellite ◽  
Navigation Accuracy

The strategic position of the polar area and its rich natural resources are becoming increasingly important, while the northeast and northwest passages through the Arctic are receiving much attention as glaciers continue to melt. The global navigation satellite system (GNSS) can provide real-time observation data for the polar areas, but may suffer low elevation problems of satellites, signals with poor carrier-power-to-noise-density ratio (C/N0), ionospheric scintillations, and dynamic requirements. In order to improve the navigation performance in polar areas, a deep-coupled navigation system with dual-frequency GNSS and a grid strapdown inertial navigation system (SINS) is proposed in the paper. The coverage and visibility of the GNSS constellation in polar areas are briefly reviewed firstly. Then, the joint dual-frequency vector tracking architecture of GNSS is designed with the aid of grid SINS information, which can optimize the tracking band, sharing tracking information to aid weak signal channels with strong signal channels and meet the dynamic requirement to improve the accuracy and robustness of the system. Besides this, the ionosphere-free combination of global positioning system (GPS) L1 C/A and L2 signals is used in the proposed system to further reduce ionospheric influence. Finally, the performance of the system is tested using a hardware simulator and semiphysical experiments. Experimental results indicate that the proposed system can obtain a better navigation accuracy and robust performance in polar areas.

scholarly journals Improved Ultra-Rapid UT1-UTC Determination and Its Preliminary Impact on GNSS Satellite Ultra-Rapid Orbit Determination

2020 ◽  
Vol 12 (21) ◽  
pp. 3584
Author(s):  
Fei Ye ◽  
Yunbin Yuan ◽  
Zhiguo Deng
Keyword(s):  
Piecewise Linear ◽  
Satellite System ◽  
Assessment System ◽  
Least Square ◽  
Linear Functions ◽  
Observation Data ◽  
Combination Model ◽  
New Strategy ◽  
Global Navigation Satellite ◽  
Traditional Strategy

Errors in ultra-rapid UT1-UTC primarily affect the overall rotation of spatial datum expressed by GNSS (Global Navigation Satellite System) satellite ultra-rapid orbit. In terms of existing errors of traditional strategy, e.g., piecewise linear functions, for ultra-rapid UT1-UTC determination, and the requirement to improve the accuracy and consistency of ultra-rapid UT1-UTC, the potential to improve the performance of ultra-rapid UT1-UTC determination based on an LS (Least Square) + AR (Autoregressive) combination model is explored. In this contribution, based on the LS+AR combination model and by making joint post-processing/rapid UT1-UTC observation data, we propose a new strategy for ultra-rapid UT1-UTC determination. The performance of the new strategy is subsequently evaluated using data provided by IGS (International GNSS Services), iGMAS (international GNSS Monitoring and Assessment System), and IERS (International Earth Rotation and Reference Systems Service). Compared to the traditional strategy, the numerical results over more than 1 month show that the new strategy improved ultra-rapid UT1-UTC determination by 29–43%. The new strategy can provide a reference for GNSS data processing to improve the performance of ultra-rapid products.

Autonomous Navigation of a Mobile Robot Based on GNSS/DR Integration in Outdoor Environments

2014 ◽  
Vol 26 (2) ◽  
pp. 214-224 ◽  
Author(s):  
Taro Suzuki ◽  
◽  
Mitsunori Kitamura ◽  
Yoshiharu Amano ◽  
Nobuaki Kubo ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Dead Reckoning ◽  
Satellite System ◽  
Mobile Robot Navigation ◽  
Observation Data ◽  
Multipath Mitigation ◽  
Ir Camera ◽  
Outdoor Environments ◽  
Global Navigation Satellite

This paper describes the development of a mobile robot system and an outdoor navigationmethod based on global navigation satellite system (GNSS) in an autonomous mobile robot navigation challenge, called the Tsukuba Challenge, held in Tsukuba, Japan, in 2011 and 2012. The Tsukuba Challenge promotes practical technologies for autonomous mobile robots working in ordinary pedestrian environments. Many teams taking part in the Tsukuba Challenge used laser scanners to determine robot positions. GNSS was not used in localization because its positioning has multipath errors and problems in availability. We propose a technique for realizing multipath mitigation that uses an omnidirectional IR camera to exclude “invisible” satellites, i.e., those entirely obstructed by a building and whose direct waves therefore are not received. We applied GPS / dead reckoning (DR) integrated based on observation data from visible satellites determined by the IR camera. Positioning was evaluated during Tsukuba Challenge 2011 and 2012. Our robot ran the 1.4 km course autonomously and evaluation results confirmed the effectiveness of our proposed technique and the feasibility of its highly accurate positioning.

scholarly journals A Method to Improve the Distribution of Observations in GNSS Water Vapor Tomography

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2526 ◽  
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Junbo Shi ◽  
Lv Zhou ◽  
Yi Xu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Absolute Error ◽  
Satellite System ◽  
Observation Data ◽  
Radiosonde Station ◽  
Satellite Signal ◽  
Comparative Results ◽  
Global Navigation Satellite ◽  
Vapor Distribution

Water vapor is an important driving factor in the related weather processes in the troposphere, and its temporal-spatial distribution and change are crucial to the formation of cloud and rainfall. Global Navigation Satellite System (GNSS) water vapor tomography, which can reconstruct the water vapor distribution using GNSS observation data, plays an increasingly important role in GNSS meteorology. In this paper, a method to improve the distribution of observations in GNSS water vapor tomography is proposed to overcome the problem of the relatively concentrated distribution of observations, enable satellite signal rays to penetrate more tomographic voxels, and improve the issue of overabundance of zero elements in a tomographic matrix. Numerical results indicate that the accuracy of the water vapor tomography is improved by the proposed method when the slant water vapor calculated by GAMIT is used as a reference. Comparative results of precipitable water vapor (PWV) and water vapor density (WVD) profiles from radiosonde station data indicate that the proposed method is superior to the conventional method in terms of the mean absolute error (MAE), standard deviations (STD), and root-mean-square error (RMS). Further discussion shows that the ill-condition of tomographic equation and the richness of data in the tomographic model need to be discussed separately.

An Improved Adaptive Evolutionary Algorithm for Multi-Objective Optimization

2013 ◽  
Vol 303-306 ◽  
pp. 1494-1500
Author(s):  
Jian Wei Wang ◽  
Jian Ming Zhang
Keyword(s):  
Evolutionary Algorithm ◽  
Optimal Solution ◽  
Optimization Methods ◽  
Relative Fitness ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fitness Value ◽  
Crossover Probability ◽  
Optimal Solution Set ◽  
Adaptive Evolutionary Algorithms

Aiming at effectively overcoming the disadvantages of traditional evolutionary algorithm which converge slowly and easily run into local extremism, an improved adaptive evolutionary algorithms is proposed. Firstly, in order to choose the optimal objective fitness value from the population in every generation, the absolute and relative fitness are defined. Secondly, fuzzy technique is adopted to adjust the weights of objective functions, crossover probability, mutation probability, crossover positions and mutation positions during the iterative process. Finally, three classical test functions are given to illustrate the validity of improved adaptive evolutionary algorithm, simulation results show that the diversity and practicability of the optimal solution set are better by using the proposed method than other multi-objective optimization methods.

scholarly journals Decomposition Multi-Objective Evolutionary Algorithm Based on Adaptive Neighborhood Adjustment Strategy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 78639-78651
Author(s):  
Liping Wang ◽  
Mengna Xu ◽  
Wei Yu ◽  
Qicang Qiu ◽  
Feng Wu
Keyword(s):  
Evolutionary Algorithm ◽  
Multi Objective ◽  
Adjustment Strategy ◽  
Adaptive Neighborhood

scholarly journals Investigation of Unmanned Aerial Vehicles-Based Photogrammetry for Large Mine Subsidence Monitoring

Minerals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 196 ◽  
Author(s):  
Danijela Ignjatović Stupar ◽  
Janez Rošer ◽  
Milivoj Vulić
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Coal Mine ◽  
Negative Impact ◽  
Local Environment ◽  
Satellite System ◽  
Reference Points ◽  
Coal Extraction ◽  
Observation Data ◽  
Aerial Vehicles ◽  
Global Navigation Satellite

With the exploitation of underground sources, nature receives a huge negative impact on the local environment introducing surface subsidence. A mining region needs to be observed in sequences before, during, and after coal extraction from the coal mine. Different measuring methods exist to monitor subsidence, and all of them apply various instrumentation. A choice of methodology depends on access to a field of observation and requested accuracy. Obviously, the most accurate results provide geometric leveling, but, many times, the terrain does not allow surveyors to walk over the dangerous outfields. Looking for the most adequate and feasible method, this research did a comparison between observation of the same points, applying statistical analysis of differences between the reference points heights, and tested methods. Monitoring procedure comprised utilization of total stations (TS), global navigation satellite system (GNSS), and unmanned aerial vehicles (UAV). In this paper, the Velenje coal mine was taken as a case study, and observation data were collected during 2017.

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