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An Improved DV-Hop Localization Algorithm Based on Hop Distances Correction 认领 引用 被引量：10
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作者 Guiqi Liu Zhihong Qian Xue Wang 《China Communications》 SCIE CSCD 2019年第6期200-214,共15页
DV-Hop localization algorithm has greater localization error which estimates distance from an unknown node to the different anchor nodes by using estimated average size of a hop to achieve the location of the unknown ... DV-Hop localization algorithm has greater localization error which estimates distance from an unknown node to the different anchor nodes by using estimated average size of a hop to achieve the location of the unknown node.So an improved DV-Hop localization algorithm based on correctional average size of a hop,HDCDV-Hop algorithm,is proposed.The improved algorithm corrects the estimated distance between the unknown node and different anchor nodes based on fractional hop count information and relatively accurate coordinates of the anchor nodes information,and it uses the improved Differential Evolution algorithm to get the estimate location of unknown nodes so as to further reduce the localization error.Simulation results show that our proposed algorithm have lower localization error and higher localization accuracy compared with the original DV-Hop algorithm and other classical improved algorithms. 展开更多
关键词 WSN DV-Hop localization algorithm Hop Distance Correction improved Differential Evolution algorithm
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Localization of Acoustic Emission Source in Rock Using SMIGWO Algorithm 认领 引用 被引量：2
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作者 Jiong Wei Fuqiang Gao +2 位作者 Jinfu Lou Lei Yang Xiaoqing Wang 《International Journal of Coal Science & Technology》 SCIE EI CAS CSCD 2025年第2期42-51,共10页
The Grey Wolf Optimization(GWO)algorithm is acknowledged as an effective method for rock acoustic emission localization.However,the conventional GWO algorithm encounters challenges related to solution accuracy and con... The Grey Wolf Optimization(GWO)algorithm is acknowledged as an effective method for rock acoustic emission localization.However,the conventional GWO algorithm encounters challenges related to solution accuracy and convergence speed.To address these concerns,this paper develops a Simplex Improved Grey Wolf Optimizer(SMIGWO)algorithm.The randomly generating initial populations are replaced with the iterative chaotic sequences.The search process is optimized using the convergence factor optimization algorithm based on the inverse incompleteГfunction.The simplex method is utilized to address issues related to poorly positioned grey wolves.Experimental results demonstrate that,compared to the conventional GWO algorithm-based AE localization algorithm,the proposed algorithm achieves a higher solution accuracy and showcases a shorter search time.Additionally,the algorithm demonstrates fewer convergence steps,indicating superior convergence efficiency.These findings highlight that the proposed SMIGWO algorithm offers enhanced solution accuracy,stability,and optimization performance.The benefits of the SMIGWO algorithm extend universally across various materials,such as aluminum,granite,and sandstone,showcasing consistent effectiveness irrespective of material type.Consequently,this algorithm emerges as a highly effective tool for identifying acoustic emission signals and improving the precision of rock acoustic emission localization. 展开更多
关键词 Acoustic emission Source localization Iterative chaotic mapping Simplex method Grey wolf optimizer algorithm
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3D numerical manifold method for crack propagation in rock materials using a local tracking algorithm 认领 引用 被引量：1
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作者 Boyi Su Tao Xu +3 位作者 Genhua Shi Michael J.Heap Xianyang Yu Guanglei Zhou 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第6期3449-3463,共15页
The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock mater... The modeling of crack growth in three-dimensional(3D)space poses significant challenges in rock mechanics due to the complex numerical computation involved in simulating crack propagation and interaction in rock materials.In this study,we present a novel approach that introduces a 3D numerical manifold method(3D-NMM)with a geometric kernel to enhance computational efficiency.Specifically,the maximum tensile stress criterion is adopted as a crack growth criterion to achieve strong discontinuous crack growth,and a local crack tracking algorithm and an angle correction technique are incorporated to address minor limitations of the algorithm in a 3D model.The implementation of the program is carried out in Python,using object-oriented programming in two independent modules:a calculation module and a crack module.Furthermore,we propose feasible improvements to enhance the performance of the algorithm.Finally,we demonstrate the feasibility and effectiveness of the enhanced algorithm in the 3D-NMM using four numerical examples.This study establishes the potential of the 3DNMM,combined with the local tracking algorithm,for accurately modeling 3D crack propagation in brittle rock materials. 展开更多
关键词 3D numerical manifold method(3D NMM) Crack propagation Local tracking algorithm Brittle materials
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High speed robust image registration and localization using optimized algorithm and its performances evaluation 认领 引用 被引量：14
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作者 Meng An Zhiguo Jiang Danpei Zhao 《Journal of Systems Engineering and Electronics》 SCIE EI 2010年第3期520-526,共7页
Local invariant algorithm applied in downward-looking image registration,usually computes the camera's pose relative to visual landmarks.Generally,there are three requirements in the process of image registration ... Local invariant algorithm applied in downward-looking image registration,usually computes the camera's pose relative to visual landmarks.Generally,there are three requirements in the process of image registration when using these approaches.First,the algorithm is apt to be influenced by illumination.Second,algorithm should have less computational complexity.Third,the depth information of images needs to be estimated without other sensors.This paper investigates a famous local invariant feature named speeded up robust feature(SURF),and proposes a highspeed and robust image registration and localization algorithm based on it.With supports from feature tracking and pose estimation methods,the proposed algorithm can compute camera poses under different conditions of scale,viewpoint and rotation so as to precisely localize object's position.At last,the study makes registration experiment by scale invariant feature transform(SIFT),SURF and the proposed algorithm,and designs a method to evaluate their performances.Furthermore,this study makes object retrieval test on remote sensing video.For there is big deformation on remote sensing frames,the registration algorithm absorbs the Kanade-Lucas-Tomasi(KLT)3-D coplanar calibration feature tracker methods,which can localize interesting targets precisely and efficiently.The experimental results prove that the proposed method has a higher localization speed and lower localization error rate than traditional visual simultaneous localization and mapping(vSLAM)in a period of time. 展开更多
关键词 local invariant features speeded up robust feature(SURF) Harris corner Kanada-Lucas-Tomasi(KLT)transform Coplanar camera calibration algorithm landmarks.
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Hybrid ToA and IMU indoor localization system by various algorithms 认领 引用 被引量：4
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作者 CHEN Xue-chen CHU Sheng +1 位作者 LI Fan CHU Guang 《Journal of Central South University》 SCIE EI CAS CSCD 2019年第8期2281-2294,共14页
In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accele... In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line. 展开更多
关键词 indoor localization time of arrival (ToA) inertial measurement unit (IMU) Bayesian filter extended Kalman filter MAP algorithm
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Immune evolutionary algorithms with domain knowledge for simultaneous localization and mapping 认领 引用 被引量：4
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作者 李枚毅 蔡自兴 《Journal of Central South University of Technology》 2006年第5期529-535,共7页
Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were de... Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms. 展开更多
关键词 immune evolutionary algorithms simultaneous localization and mapping domain knowledge
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A Semi-Supervised WLAN Indoor Localization Method Based on l1-Graph Algorithm 认领 引用 被引量：1
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作者 Liye Zhang Lin Ma Yubin Xu 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2015年第4期55-61,共7页
For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be colle... For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be collected in offline phase. Therefore,collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper,the traditional semisupervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed,and the result shows that the k-NN or ε-NN graph are sensitive to data noise,which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem,it proposes a l1-graph-algorithm-based semi-supervised learning( LG-SSL) indoor localization method in which the graph is built by l1-norm algorithm. In our system,it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase,and then uses LG-SSL to estimate user's location in online phase. Extensive experimental results show that,benefit from the robustness to noise and sparsity ofl1-graph,LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase. 展开更多
关键词 indoor location estimation l1-graph algorithm semi-supervised learning wireless local area networks(WLAN)
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Modified Levenberg-Marquardt algorithm for source localization using AOAs in the presence of sensor location errors 认领 引用
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作者 吴鑫辉 Huang Gaoming Gao Jun 《High Technology Letters》 EI CAS 2014年第3期274-281,共8页
In this paper,by utilizing the angle of arrivals(AOAs) and imprecise positions of the sensors,a novel modified Levenberg-Marquardt algorithm to solve the source localization problem is proposed.Conventional source loc... In this paper,by utilizing the angle of arrivals(AOAs) and imprecise positions of the sensors,a novel modified Levenberg-Marquardt algorithm to solve the source localization problem is proposed.Conventional source localization algorithms,like Gauss-Newton algorithm and Conjugate gradient algorithm are subjected to the problems of local minima and good initial guess.This paper presents a new optimization technique to find the descent directions to avoid divergence,and a trust region method is introduced to accelerate the convergence rate.Compared with conventional methods,the new algorithm offers increased stability and is more robust,allowing for stronger non-linearity and wider convergence field to be identified.Simulation results demonstrate that the proposed algorithm improves the typical methods in both speed and robustness,and is able to avoid local minima. 展开更多
关键词 source localization angle of arrivals （AOAs） nonlinear least-squares estimators Levenberg-Marquardt algorithm
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Research on localization algorithm of naval vessel for submarine based on bearing-range measurements 认领 引用
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作者 崔旭涛 杨日杰 何友 《Journal of Measurement Science and Instrumentation》 CAS 2012年第1期10-13,共4页
Combined with naval vessel practical antisubmarine equipment of towed linear array sonar,a mathematical model of naval vessel localization for submarine based on bearing measurement was built,and localization algorith... Combined with naval vessel practical antisubmarine equipment of towed linear array sonar,a mathematical model of naval vessel localization for submarine based on bearing measurement was built,and localization algorithm was given to solve submarine movement parameters.Localizaiton errors were analyzed.Based on localization model and algorithm,simulations were done to study the effect of factors such as initial distance between submarine and the naval vessel,submarine initial bearing angle measured by the naval vessel and submarine course on localization performance,and then simulation results were given and analyzed.The results have practical value to instruct real antisubmarine.Simulation results show that different target movement situations have great influence on sonar detection and localization performance,so the reasonable choice of sonar position and detection bearing according to the target movement situation can improve sonar detection and localization performance to some degree. 展开更多
关键词 naval vessel bearing measurement submarine localization error analysis localization algorithm
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A Localization Algorithm Using a Mobile Anchor Node Based on Region Determination in Underwater Wireless Sensor Networks 认领 引用 被引量：9
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作者 XU Tingting WANG Jingjing +2 位作者 SHI Wei WANG Jianfeng CHEN Zhe 《Journal of Ocean University of China》 SCIE CAS CSCD 2019年第2期394-402,共9页
At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper propo... At present, most underwater positioning algorithms improve the positioning accuracy by increasing the number of anchor nodes which resulting in the increasing energy consumption. To solve this problem, the paper proposes a localization algorithm assisted by mobile anchor node and based on region determination(LMRD), which not only improves the positioning accuracy of nodes positioning but also reduces the energy consumption. This algorithm is divided into two stages: region determination stage and location positioning stage. In the region determination stage, the target region is divided into several sub-regions by the region division strategy with the smallest overlap rate which can reduce the number of virtual anchor nodes and lock the target node to a sub-region, and then through the planning of mobile nodes to optimize the travel path, reduce the moving distance, and reduce system energy consumption. In the location positioning stage, the target node location can be calculated using the HILBERT path planning and trilateration. The simulation results show that the proposed algorithm can improve the positioning accuracy when the energy consumption is reduced. 展开更多
关键词 UWSN mobile anchor nodes energy consumption region determination localization algorithm
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New Iris Localization Method Based on Chaos Genetic Algorithm 认领 引用
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作者 贾东立 Muhammad Khurram Khan 张家树 《Journal of Southwest Jiaotong University(English Edition)》 2005年第1期35-38,共4页
This paper present a new method based on Chaos Genetic Algorithm (CGA) to localize the human iris in a given image. First, the iris image is preprocessed to estimate the range of the iris localization, and then CGA is... This paper present a new method based on Chaos Genetic Algorithm (CGA) to localize the human iris in a given image. First, the iris image is preprocessed to estimate the range of the iris localization, and then CGA is used to extract the boundary of the ~iris . Simulation results show that the proposed algorithms is efficient and robust, and can achieve sub pixel precision. Because Genetic Algorithms (GAs) can search in a large space, the algorithm does not need accurate estimation of iris center for subsequent localization, and hence can lower the requirement for original iris image processing. On this point, the present localization algirithm is superior to Daugman's algorithm. 展开更多
关键词 Chaos genetic algorithm Iris localization Geometric primitive extraction
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Convex Optimization Algorithms for Cooperative Localization in Autonomous Underwater Vehicles 认领 引用 被引量：10
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作者 LIU Ming-Yong LI Wen-Bai PEI Xuan 《自动化学报》 EI CAS 北大核心 2010年第5期704-710,共7页
In this paper,a cooperative localization algorithm for autonomous underwater vehicles(AUVs)is proposed.A"parallel"model is adopted to describe the cooperative localization problem instead of the traditional&... In this paper,a cooperative localization algorithm for autonomous underwater vehicles(AUVs)is proposed.A"parallel"model is adopted to describe the cooperative localization problem instead of the traditional"leader-follower"model,and a linear programming associated with convex optimization method is used to deal with the problem.After an unknown-but-bounded model for sensor noise is assumed,bearing and range measurements can be modeled as linear constraints on the configuration space of the AUVs.Merging these constraints induces a convex polyhedron representing the set of all configurations consistent with the sensor measurements.Estimates for the uncertainty in the position of a single AUV or the relative positions of two or more nodes can then be obtained by projecting this polyhedron onto appropriate subspaces of the configuration space.Two different optimization algorithms are given to recover the uncertainty region according to the number of the AUVs.Simulation results are presented for a typical localization example of the AUV formation.The results show that our positioning method offers a good localization accuracy,although a small number of low-cost sensors are needed for each vehicle,and this validates that it is an economical and practical positioning approach compared with the traditional approach. 展开更多
关键词 Autonomous underwater vehicle(AUV) convex optimization cooperative localization uncertainty region screening algorithm approximation algorithm
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A Fuzzy Decision Based WSN Localization Algorithm for Wise Healthcare 认领 引用 被引量：2
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作者 Jiangyu Yan Ran Qiao +2 位作者 Liangrui Tang Chenxi Zheng Bing Fan 《China Communications》 SCIE CSCD 2019年第4期208-218,共11页
Wise healthcare is a typical application of wireless sensor network(WSN), which uses sensors to monitor the physiological state of nursing targets and locate their position in case of an emergency situation. The locat... Wise healthcare is a typical application of wireless sensor network(WSN), which uses sensors to monitor the physiological state of nursing targets and locate their position in case of an emergency situation. The location of targets need to be determined and reported to the control center,and this leads to the localization problem. While localization in healthcare field demands high accuracy and regional adaptability, the information processing mechanism of human thinking has been introduced,which includes knowledge accumulation, knowledge fusion and knowledge expansion. Furthermore, a fuzzy decision based localization approach is proposed. Received signal strength(RSS) at references points are obtained and processed as position relationship indicators, using fuzzy set theory in the knowledge accumulation stage; after that, optimize degree of membership corresponding to each anchor nodes in different environments during knowledge fusion; the matching degree of reference points is further calculated and sorted in decision-making, and the coordinates of several points with the highest matching degree are utilized to estimate the location of unknown nodes while knowledge expansion. Simulation results show that the proposed algorithm get better accuracy performance compared to several traditional algorithms under different typical occasions. 展开更多
关键词 WSN localization wise healthcare fuzzy decision algorithm reference points matching degree
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Improved Algorithm for Distributed Localization in Wireless Sensor Networks 认领 引用 被引量：6
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作者 钟幼平 匡兴红 黄佩伟 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第1期64-69,共6页
Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typical... Many sensor network applications require location awareness,but it is often too expensive to equip a global positioning system(GPS) receiver for each network node.Hence,localization schemes for sensor networks typically use a small number of seed nodes that know their locations and protocols whereby other nodes estimate their locations from the messages they receive.For the inherent shortcomings of general particle filter(the sequential Monte Carlo method) this paper introduces particle swarm optimization and weighted centroid algorithm to optimize it.Based on improvement a distributed localization algorithm named WC-IPF(weighted centroid algorithm improved particle filter) has been proposed for localization.In this localization scheme the initial estimate position can be acquired by weighted centroid algorithm.Then the accurate position can be gotten via improved particle filter recursively.The extend simulation results show that the proposed algorithm is efficient for most condition. 展开更多
关键词 wireless sensor network node localization particle filter particle swarm optimization weighted centroid algorithm
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An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm 认领 引用 被引量：2
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作者 Thi-Kien Dao Trong-The Nguyen 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第3期2201-2237,共37页
Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand... Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging andfundamental operations in various monitoring or tracking applications because the network deploys a large areaand allocates the acquired location information to unknown devices. The metaheuristic approach is one of themost advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditionalmethods that often suffer from computational time problems and small network deployment scale. This studyproposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on thesiege mechanism (SWOA) for node localization inWSN. The objective function is modeled while communicatingon localized nodes, considering variables like delay, path loss, energy, and received signal strength. The localizationapproach also assigns the discovered location data to unidentified devices with the modeled objective functionby applying the SWOA algorithm. The experimental analysis is carried out to demonstrate the efficiency of thedesigned localization scheme in terms of various metrics, e.g., localization errors rate, converges rate, and executedtime. Compared experimental-result shows that theSWOA offers the applicability of the developed model forWSNto perform the localization scheme with excellent quality. Significantly, the error and convergence values achievedby the SWOA are less location error, faster in convergence and executed time than the others compared to at least areduced 1.5% to 4.7% error rate, and quicker by at least 4%and 2% in convergence and executed time, respectivelyfor the experimental scenarios. 展开更多
关键词 Node localization whale optimization algorithm wireless sensor networks siege whale optimization algorithm optimization
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An Improved Underwater Acoustic Network Localization Algorithm 认领 引用 被引量：5
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作者 WU Zhehao LI Xia 《China Communications》 SCIE CSCD 2015年第3期77-83,共7页
Underwater sensor network can achieve the unmanned environmental monitoring and military monitoring missions.Underwater acoustic sensor node cannot rely on the GPS to position itself,and the traditional indirect posit... Underwater sensor network can achieve the unmanned environmental monitoring and military monitoring missions.Underwater acoustic sensor node cannot rely on the GPS to position itself,and the traditional indirect positioning methods used in Ad Hoc networks are not fully applicable to the localization of underwater acoustic sensor networks.In this paper,we introduce an improved underwater acoustic network localization algorithm.The algorithm processes the raw data before localization calculation to enhance the tolerance of random noise.We reduce the redundancy of the calculation results by using a more accurate basic algorithm and an adjusted calculation strategy.The improved algorithm is more suitable for the underwater acoustic sensor network positioning. 展开更多
关键词 acoustic sensor network localization algorithm greedy algorithm interval estimation
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Three-Dimensional Distance-Error-Correction-Based Hop Localization Algorithm for IoT Devices 认领 引用
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作者 Deepak Prashar Gyanendra Prasad Joshi +2 位作者 Sudan Jha Eunmok Yang Kwang Chul Son 《Computers, Materials & Continua》 SCIE EI 2021年第2期1529-1549,共21页
The Internet of Things(IoT)is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems.These networks of wireless sensors monitor... The Internet of Things(IoT)is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems.These networks of wireless sensors monitor the physical environment and report the collected data to the base station,allowing for smarter decisions.Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane.However,in some application areas,such as various surveillances,underwater monitoring systems,and various environmental monitoring applications,wireless sensors are deployed in a three-dimensional plane.Recently,localization-based applications have emerged as one of the most promising services related to IoT.In this paper,we propose a novel distributed range-free algorithm for node localization in wireless sensor networks.The proposed three-dimensional hop localization algorithm is based on the distance error correction factor.In this algorithm,the error decreases with the localization process.The distance correction factor is used at various stages of the localization process,which ultimately mitigates the error.We simulated the proposed algorithm using MATLAB and verified the accuracy of the algorithm.The simulation results are compared with some of the well-known existing algorithms in the literature.The results show that the proposed three-dimensional error-correctionbased algorithm performs better than existing algorithms. 展开更多
关键词 3D localization DV-hop algorithm IoT PSO wireless sensor networks
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A Localization Algorithm in Wireless Sensor Network Based on Positioning Group Quality 认领 引用
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作者 Kaiguo Qian Chunfen Pu +2 位作者 Yujian Wang Shaojun Yu Shikai Shen 《国际计算机前沿大会会议论文集》 EI 2021年第1期125-139,共15页
Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy f... Localization is fundamental component for many critical applicationsin wireless sensor networks (WSNs). However, DV-Hop localization algorithmand its improved ones cannot meet the requirement of positioning accuracy fortheir high localization errors. This paper proposes a localization algorithm basedon positioning group quality (LA-PGQ). The average estimate hop size was firstcorrected by link singularity and difference between the estimation hop lengthand true hop length among beacons, the best positioning group was constitutedfor unknown node by using node trust function and positioning group qualityevaluation function to choose three beacons with best topological distribution.Third, LA-PGQ algorithm uses two-dimensional hyperbolic algorithm instead ofthe classical three-side method/least square method to determine the coordinates ofnodes, which are more accurate. Simulation results show the positioning accuracyof LA-PGQ algorithm is obviously improved in WSNs, and the average localizationerror of LA-PGQ algorithm is remarkable lower than those of the DV-Hopalgorithm and its improved algorithm and Amorphous, under both the isotropyand anisotropy distributions. 展开更多
关键词 Wireless sensor networks Localization algorithm Positioning group quality Positioning accuracy
Localization Algorithm of Wireless Sensor Network Based on Concentric Circle Distance Calculation 认领 引用
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作者 KaiGuo Qian Chunfen Pu +2 位作者 Yujian Wang ShaoJun Yu Shikai Shen 《国际计算机前沿大会会议论文集》 EI 2020年第1期405-415,共11页
Node Localization is one of the key technology in the field of wireless sensor network(WSN)that has become a challenging research topic under the lack of distance measurement.In order to solve this problem,a localizat... Node Localization is one of the key technology in the field of wireless sensor network(WSN)that has become a challenging research topic under the lack of distance measurement.In order to solve this problem,a localization algorithm based on concentric circle distance calculation(LACCDC)is proposed.The LA-CCDC takes the beacon as the center of the concentric circle,then divides the task area into concentric circles with the k communication radius of sensor,which forms concentric rings.The node located in the k hops ring intersects the concentric circle with(k−1)r radius that forms an intersection area.This area is used to calculate the distance from the beacon to the unknown node,hyperbola is then adopted to locate the unknown node.In the application scenario with node random distribution,the simulation results show that the LA-CCDC algorithm gets the node location with low error under different node number,different beacons and different communication radius of sensor. 展开更多
关键词 Wireless sensor network(WSN) Localization algorithm Concentric circles Average relative positioning error(ARPE)
Analysis of Five Typical Localization Algorithms for Wireless Sensor Networks 认领 引用 被引量：5
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作者 Shelei Li Xueyong Ding Tingting Yang 《Wireless Sensor Network》 2015年第4期27-33,共7页
In this paper, the self-localization problem is studied. It is one of the key technologies in wireless sensor networks (WSNs). And five localization algorithms: Centroid algorithm, Amorphous algorithm, DV-hop algorith... In this paper, the self-localization problem is studied. It is one of the key technologies in wireless sensor networks (WSNs). And five localization algorithms: Centroid algorithm, Amorphous algorithm, DV-hop algorithm, APIT algorithm and Bounding Box algorithm are discussed. Simulation of those five localization algorithms is done by MATLAB. The simulation results show that the positioning error of Amorphous algorithm is the minimum. Considering economy and localization accuracy, the Amorphous algorithm can achieve the best localization performance under certain conditions. 展开更多
关键词 Wireless Sensor Networks (WSNs) Localization Algorithm Centroid Amorphous DV-Hop APIT Bounding Box
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