The Weighted Localization Algorithm Based on RSSI Calibration

2012 ◽  
Vol 236-237 ◽  
pp. 1010-1014
Author(s):  
Ning Hui He ◽  
Hong Sheng Li ◽  
Guang Rong Bian
Keyword(s):  
Wireless Sensor Network ◽  
Signal Strength ◽  
The Other ◽  
Wireless Sensor ◽  
Network Node ◽  
Localization Algorithm ◽  
Node Localization ◽  
Positioning Accuracy ◽  
Location Algorithm ◽  
Beacon Node

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.

The Improved Personnel Location Algorithm Based on RSSI

2013 ◽  
Vol 712-715 ◽  
pp. 2003-2006
Author(s):  
Sheng Mei Zhou ◽  
Ting Lei Huang
Keyword(s):  
Signal Strength ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Matlab Simulation ◽  
Node Localization ◽  
Received Signal Strength Indicator ◽  
Positioning Accuracy ◽  
Location Algorithm ◽  
Non Line Of Sight

In the process of that based on the RSSI received signal strength indicator technique, resulting in the positioning accuracy is so low, since the simple RSSI, multipath, diffraction and non line of sight and other factors. In order to achieve higher accuracy node localization in wireless sensor, the paper is proposed based on the probability of recycling triangle centroid location algorithm in the RSSI technique,The probability of the cycle to handle triangle centroid localization algorithm. Through the Matlab simulation, compared with the traditional triangle centroid localization algorithm, the error is significantly reduced and positioning accuracy improved when the anchor point number exceeds a certain number.

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
Keyword(s):  
Wireless Sensor Network ◽  
Curve Fitting ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Centroid Algorithm ◽  
Key Technologies ◽  
Accurate Position ◽  
Beacon Node ◽  
Range Free

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.

Study on Node Localization Algorithms in Wireless Sensor Network

2014 ◽  
Vol 556-562 ◽  
pp. 3952-3955
Author(s):  
Jian Deng
Keyword(s):  
Wireless Sensor Network ◽  
Coordinate System ◽  
Local Coordinate System ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Node Localization ◽  
Positioning Accuracy ◽  
Localization Algorithms ◽  
The Difference ◽  
Localization Information

This paper introduces an improved localization algorithm that bases on distance and local coordinate system which is built up by beacon nodes. This algorithm evaluates the differences of several independent localization information to determine whether upgrade this node as beacon nodes according to the size of the difference whether beyond the prescribed or not. It can effectively prevent and reduce the accumulated and spread error in localization process by the audit of beacon nodes, and improve the positioning accuracy of nodes in the network.

A Study of Mobile Node Localization Algorithm Based on Ranging MCL for WSN

2012 ◽  
Vol 182-183 ◽  
pp. 2012-2018
Author(s):  
Wei Dong Tang ◽  
Bai Liu ◽  
Chao Qun Zhang ◽  
Jin Zhao Wu
Keyword(s):  
Wireless Sensor Network ◽  
Simulation Analysis ◽  
Mobile Node ◽  
Wireless Sensor ◽  
Motion Model ◽  
Localization Algorithm ◽  
Node Localization ◽  
Node Density ◽  
Positioning Accuracy ◽  
Key Technologies

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.

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