An Improved DV-HOP Localization Algorithm Based on Simulation Curve Fitting

2013 ◽  
Vol 684 ◽  
pp. 390-393 ◽  
Author(s):  
Lin Chen ◽  
Zhi Yi Fang ◽  
Wei Lv ◽  
Zhuang Liu

Localization technology is one of the key technologies in Wireless Sensor Network (WSN). The Centroid algorithm, DV-HOP algorithm, APIT algorithm and Amorphous are the classic algorithms which are based on Range-free localization algorithm. This paper is improved on the basis of the DV-HOP and Weighted DV-HOP node localization algorithm, proposed an improved DV-HOP and weighted DV-HOP of WSN localization algorithm based on Simulation Curve Fitting (SCF). The SCF algorithm makes the process more refined during selecting the beacon node and the selected beacon node can be closer to the accurate position.

2012 ◽  
Vol 236-237 ◽  
pp. 1010-1014
Author(s):  
Ning Hui He ◽  
Hong Sheng Li ◽  
Guang Rong Bian

This paper introduces the first wireless sensor network node localization in two ways, one is based on the RSSI ranging approach, and the other is based on the weighted centric location algorithm, as a result of environmental factors, the same RSSI value the distance ,but the corresponding values are not always the same, these two methods do not consider the environmental impact to the RSSI value. Therefore, we consider combining the distance and signal strength information as a reference to correct each beacon node weights, in order to improve positioning accuracy.


2014 ◽  
Vol 543-547 ◽  
pp. 3256-3259 ◽  
Author(s):  
Da Peng Man ◽  
Guo Dong Qin ◽  
Wu Yang ◽  
Wei Wang ◽  
Shi Chang Xuan

Node Localization technology is one of key technologies in wireless sensor network. DV-Hop localization algorithm is a kind of range-free algorithm. In this paper, an improved DV-Hop algorithm aiming to enhance localization accuracy is proposed. To enhance localization accuracy, average per-hop distance is replaced by corrected value of global average per-hop distance and global average per-hop error. When calculating hop distance, unknown nodes use corresponding average per-hop distance expression according to different hop value. Comparison with DV-Hop algorithm, simulation results show that the improved DV-Hop algorithm can reduce the localization error and enhance the accuracy of sensor nodes localization more effectively.


2012 ◽  
Vol 182-183 ◽  
pp. 2012-2018
Author(s):  
Wei Dong Tang ◽  
Bai Liu ◽  
Chao Qun Zhang ◽  
Jin Zhao Wu

Node localization is one of the key technologies in wireless sensor network. This paper proposed an improved RBDMCL algorithm based on traditional MCL algorithm, which can reduce the sampling areas and improve the positioning accuracy by building a node motion model. Then concludes by simulation analysis and comparison that RBDMCL has higher positioning accuracy than MCL in the anchor node density and node velocity.


2013 ◽  
Vol 694-697 ◽  
pp. 1055-1059
Author(s):  
Guang Xiong Huang ◽  
Zhi Long Shan

Localization is an essential technology in the application of wireless sensor network. As a range-free localization algorithm, DV-Hop works well in dense and isotropic networks, but not much in irregular and sparse topologies, especially in the big curvature of shortest path case. In this paper, location information beyond the communication range was obtained by means of variable transmission power of enhanced nodes. Besides, three schemes was proposed to meet the need of different scenarios. Moreover, the simulation results validate that our method can improve position accuracy about 20% and ameliorate the performance of DV-Hop in irregular scenario.


2013 ◽  
Vol 475-476 ◽  
pp. 579-582 ◽  
Author(s):  
Dong Yao Zou ◽  
Teng Fei Han ◽  
Dao Li Zheng ◽  
He Lv

The node localization is one of the key technologies in wireless sensor networks. To the accurate positioning of the nodes as the premise and foundation, this paper presents a centroid localization algorithm based on Cellular network. First, the anchor nodes are distributed in a regular hexagonal cellular network. Unknown nodes collect the RSSI of the unknown nodes nearby, then select the anchor nodes whose RSSI is above the threshold. Finally, the average of these anchor nodes coordinates is the positioning results. MATLAB simulation results show that localization algorithm is simple and effective, it applies to the need for hardware is relatively low.


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