scholarly journals Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jing Zhang ◽  
Yajing Hu ◽  
Hongliang Li
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor ◽  
Harsh Environment ◽  
Positioning Error ◽  
Network Construction ◽  
Maximum Coverage ◽  
Ranging Error ◽  
Anchor Nodes ◽  
Communication Constraint ◽  
Positioning Algorithm

For smart city wireless sensing network construction needs, a network positioning algorithm based on genetic algorithm is proposed. The genetic algorithm uses a real number encoding, and the positioning model is constructed by analyzing the communication constraint between unknown nodes and a small amount of anchor nodes and constructs the positioning model, and the model is solved. The results show that when the ranging error is 50%, the positioning error is only increased by approximately 15% compared to the nonranging error. In a more harsh environment, if the ranging error is equal to the node wireless range, the ranging error is 100%, and the positioning error and the positioning ratio are not significantly changed. The scheme obtained by this algorithm can be well approarded with an ideal limit. In the case where the sensor node is given, the algorithm can obtain the maximum coverage.

Optimization of the Wireless Sensor Nodes Localization Algorithm Based on Genetic Algorithm

2014 ◽  
Vol 6 (4) ◽  
pp. 55-64
Author(s):  
Tan Zhi ◽  
Zhang Yuting
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Initial Population ◽  
Localization Algorithm ◽  
Node Localization ◽  
Anchor Nodes ◽  
Reference Weight ◽  
Positioning Algorithm

The node localization technology is a foundation for practical application in wireless sensor networks. According to DV-HOP positioning algorithm in wireless sensor network low precision, the defect of inaccurate positioning, this paper presents an optimization algorithm of improved DV-HOP based on genetic algorithm. The algorithm is to redefine the scope of initial population, the reference weight, redesigned the fitness function and selection of anchor nodes. The simulation results show that compared with the traditional DV - HOP algorithm, the algorithm without any increase in the node hardware overhead on the basis of significantly higher positioning accuracy.

The Weighted Multilateral Positioning Algorithm Based on Time Reversal Ranging

2014 ◽  
Vol 644-650 ◽  
pp. 1464-1469
Author(s):  
Zheng Zhang ◽  
Xing Peng Tao ◽  
Lun Zeng ◽  
Chan Wang
Keyword(s):  
Time Reversal ◽  
Wireless Sensor ◽  
Positioning Error ◽  
Complex Environments ◽  
Complex Environment ◽  
General Applicability ◽  
Positioning Accuracy ◽  
Key Technology ◽  
Ranging Error ◽  
Positioning Algorithm

Indoor node positioning is a key technology in wireless sensor network but the general indoor nodes positioning algorithm is difficult to meet the precision positioning requirements due to the indoor complex environment such as multilateral positioning algorithm based on RSSI ranging. The weighted multilateral positioning algorithm is proposed based on time reversal ranging to solve the problem. We simulate within 50m*50m area, the experimental results show that the ranging error is less than 1%. The maximum positioning error is less than 0.6m. Compared with general positioning algorithm, it can improve the positioning accuracy greatly in complex environments and has general applicability.

scholarly journals Factor Graph-Assisted Distributed Cooperative Positioning Algorithm in the GNSS System

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3748 ◽  
Author(s):  
Chengkai Tang ◽  
Lingling Zhang ◽  
Yi Zhang ◽  
Houbing Song
Keyword(s):  
Smart Cities ◽  
Factor Graph ◽  
Positioning Error ◽  
Positioning Accuracy ◽  
Cooperative Positioning ◽  
Measured Range ◽  
Ranging Error ◽  
Positioning Algorithm ◽  
Range Error ◽  
Cooperative Nodes

The development of smart cities calls for improved accuracy in navigation and positioning services; due to the effects of satellite orbit error, ionospheric error, poor quality of navigation signals and so on, it is difficult for existing navigation technology to achieve further improvements in positioning accuracy. Distributed cooperative positioning technology can further improve the accuracy of navigation and positioning with existing GNSS (Global Navigation Satellite System) systems. However, the measured range error and the positioning error of the cooperative nodes exhibit larger reductions in positioning accuracy. In response to this question, this paper proposed a factor graph-aided distributed cooperative positioning algorithm. It establishes the confidence function of factor graphs theory with the ranging error and the positioning error of the coordinated nodes and then fuses the positioning information of the coordinated nodes by the confidence function. It can avoid the influence of positioning error and ranging error and improve the positioning accuracy of cooperative nodes. In the simulation part, the proposed algorithm is compared with a mainly coordinated positioning algorithm from four aspects: the measured range error, positioning error, convergence speed, and mutation error. The simulation results show that the proposed algorithm leads to a 30–60% improvement in positioning accuracy compared with other algorithms under the same measured range error and positioning error. The convergence rate and mutation error elimination times are only 1 / 5 to 1 / 3 of the other algorithms.

scholarly journals NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2991 ◽  
Author(s):  
Jingyu Hua ◽  
Yejia Yin ◽  
Weidang Lu ◽  
Yu Zhang ◽  
Feng Li
Keyword(s):  
Hypothesis Test ◽  
Intermediate Position ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Target Node ◽  
Localization Algorithms ◽  
Anchor Nodes ◽  
Positioning Algorithm ◽  
Non Line Of Sight

The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.

scholarly journals Exploration of Wireless Sensor Network Based on RSSI Positioning Algorithm

2018 ◽  
Vol 14 (11) ◽  
pp. 133
Author(s):  
Shuan Liu
Keyword(s):  
Signal Strength ◽  
Wireless Sensor ◽  
Positioning Error ◽  
Network Resources ◽  
Simulation Experiments ◽  
Wormhole Attack ◽  
Positioning Method ◽  
Physical Information ◽  
Positioning Algorithm ◽  
Node Energy

<p class="0abstract"><span lang="EN-US">Based on the security of the receiving signal strength indicator positioning algorithm, the RSSI positioning algorithm in the environment of witch attack, wormhole attack and replication attack has largely failed</span><span lang="EN-US">.</span><span lang="EN-US">Although existing security </span><span lang="EN-US">positioning</span><span lang="EN-US"> algorithms can effectively prevent attacks from occurring, the massive consumption of network resources can’t be ignored.</span><span lang="EN-US">Therefore, a tolerable security positioning method is proposed for each of the three attacks in order to improve the security of positioning.</span><span lang="EN-US">According to the node's physical information, the attack node is detected.</span><span lang="EN-US">Through simulation experiments, compared with the traditional indoor security </span><span lang="EN-US">positioning</span><span lang="EN-US"> method, the proposed algorithm can significantly reduce the intervention of witch attack, wormhole attack and replication attack on positioning error.</span><span lang="EN-US">While achieving the goal of combating attacks, it reduces the computational complexity, decreases node energy consumption, and extends the network life cycle.</span></p>

scholarly journals A Combined Localization Algorithm for Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaogang Qi ◽  
Xiaoke Liu ◽  
Lifang Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
State Of The Art ◽  
Sensor Nodes ◽  
Vehicle Tracking ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Environment And Health ◽  
Anchor Nodes ◽  
Positioning Algorithm

Wireless sensor networks (WSNs) are widely used in various fields to monitor and track various targets by gathering information, such as vehicle tracking and environment and health monitoring. The information gathered by the sensor nodes becomes meaningful only if it is known where it was collected from. Considering that multilateral algorithm and MDS algorithm can locate the position of each node, we proposed a localization algorithm combining the merits of these two approaches, which is called MA-MDS, to reduce the accumulation of errors in the process of multilateral positioning algorithm and improve the nodes’ positioning accuracy in WSNs. It works in more robust fashion for noise sparse networks, even with less number of anchor nodes. In the MDS positioning phase of this algorithm, the Prussian Analysis algorithm is used to obtain more accurate coordinate transformation. Through extensive simulations and the repeatable experiments under diverse representative networks, it can be confirmed that the proposed algorithm is more accurate and more efficient than the state-of-the-art algorithms.

Gravitational Particle Swarm Optimization Localization Algorithm for Wireless Sensor Network Nodes

2014 ◽  
Vol 556-562 ◽  
pp. 4622-4627
Author(s):  
Shu Wang Zhou ◽  
Ming Lei Shu ◽  
Ming Yang ◽  
Ying Long Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Method Of Least Squares ◽  
Swarm Optimization ◽  
Network Nodes ◽  
Ranging Error ◽  
Anchor Nodes ◽  
Localization Approach

A range-based localization approach which named gravitational particle swarm optimization localization algorithm (GL) has been proposed. This algorithm considered the influence from the position of anchor nodes to the localization results, GL can directly searched out the coordinates of unknown nodes by the distance from anchor nodes to unknown nodes. As is shown in the experiment results, GL not only has high positioning accuracy, but also overcomes the defect that location error increases rapidly as the ranging error increases, compares with normal schemes (such as method of least squares, ML ) GL’s accuracy can improve 40% as the ranging error is 35%.

scholarly journals Improvement of Localization Algorithm for Wireless Sensor Networks Based on DV-Hop

2019 ◽  
Vol 15 (06) ◽  
pp. 53 ◽  
Author(s):  
Xin Qiao ◽  
Fei Chang ◽  
Jing Ling
Keyword(s):  
Estimation Method ◽  
Likelihood Estimation ◽  
Mean Value ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Anchor Node ◽  
Jump Distance ◽  
Anchor Nodes ◽  
Unknown Node ◽  
Positioning Algorithm

In order to solve the problem that the DV-Hop localization algorithm has large errors in the wireless sensor network environment, this paper uses the minimum mean square criterion to determine the average hop distance of anchor nodes, and then calculates the mean value of the original average hop distance, which ensures that the improved average hop distance is closer to the real average hop distance of the whole network. The estimated distances between nodes are calculated by using the correction value corresponding to the average jump distance of the anchor node; in the positioning stage, when the anchor node is small, the estimated coordinates of unknown nodes are obtained by the minimum-maximum method; when the number of anchor nodes is large, the coordinates of unknown nodes are calculated by the maximum likelihood estimation method; this not only reduces the amount of calculation, but also the accuracy is more stable. This step is not only suitable for DV-Hop algorithm, but also can be used to estimate the coordinates when the distance between the unknown node and the anchor node is known. However, this improved method is only applicable to the premise that the simulation area is not large, so this improvement has its scope of adaptation, according to the needs of choice. Finally, the unknown node coordinates are iteratively optimized by using the quasi Newton method. Simulation results show that the proposed positioning algorithm has higher accuracy and better stability.

A Localization Algorithm of Multi-Hop Three Dimensional AOA with Space-Based Angle Transmission and its Application

2013 ◽  
Vol 756-759 ◽  
pp. 3562-3567
Author(s):  
Qing Zhang Chen ◽  
Yun Feng Ni ◽  
Xing Hua Li ◽  
Rong Jie Wu ◽  
Yan Jing Lei ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Angle Of Arrival ◽  
Terrain Modeling ◽  
Terrain Model ◽  
Anchor Nodes ◽  
Slow Progress ◽  
Positioning Algorithm

Wireless sensor node's localization is a funda-mental technology in Wireless Sensor Networks. There are only quite a few study on three-dimensional (3D) localization which is suffered in slow progress, actually, is one of the main difficulties in WSN localization. Based on the study of the existing two-dimensional positioning algorithm and the application of terrain modeling, localization algorithm for sensor nodes in (3D) condition has been focus on as well as the application of terrain model. Using the idea proposed by representative algorithm--APS multi-hop AOA (Angle of Arrival), this paper proposed a new algorithm named Multi-hop Three Dimensional AOA With Space-based Angle Trans-mission (MSAT3D AOA). Using this technology, target nodes can use information of anchor nodes which are more than one hop away form. This paper also combined MSAT3D AOA algorithm with Delaunay triangulation algorithm for terrain modeling.

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