Localization accuracy of farmland wireless sensor network localization algorithm based on received signal strength indicator

2018 ◽  
Vol 23 (5) ◽  
pp. 69-80 ◽  
Author(s):  
Yisheng MIAO ◽  
Huarui WU ◽  
Huaji ZHU ◽  
Yuling SONG
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Sensor Network Localization ◽  
Localization Accuracy ◽  
Network Localization

scholarly journals An RSSI-based Wireless Sensor Network Localization Algorithm with Error Checking and Correction

2017 ◽  
Vol 13 (12) ◽  
pp. 52 ◽  
Author(s):  
Bo Guan ◽  
Xin Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Anchor Node ◽  
Network Localization ◽  
Error Checking

<p style="margin: 1em 0px;"><span style="font-family: Times New Roman; font-size: medium;">This paper studies the wireless sensor network localization algorithm based on the received signal strength indicator (RSSI) in detail. Considering the large errors in ranging and localization of nodes made by the algorithm, this paper corrects and compensates the errors of the algorithm to improve the coordinate accuracy of the node. The improved node localization algorithm performs error checking and correction on the anchor node and the node to be measured, respectively so as to make the received signal strength value of the node to be measured closer to the real value. It corrects the weighting factor by using the measured distance between communication nodes to make the coordinate of the node to be measured more accurate. Then, it calculates the mean deviation of localization based on the anchor node close to the node to be measured and compensates the coordinate error. Through the simulation experiment, it is found that the new localization algorithm with error checking and correction proposed in this paper improves the localization accuracy by 5%-6% compared with the weighted centroid algorithm based on RSSI.</span></p>

A Localization Algorithm for Wireless Sensor Network Based on the Weighted Correction in Geometric Measurement

2015 ◽  
Vol 740 ◽  
pp. 823-829
Author(s):  
Meng Long Cao ◽  
Chong Xin Yang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Localization Algorithms ◽  
Weighted Centroid Localization ◽  
Geometric Measurement

Firstly, the characteristics of regular Zigbee localization algorithms-the received signal strength indicator algorithm (RSSI) and the weighted centroid localization algorithm are introduced. Then, the factors of the errors existing in the aforementioned algorithms are analyzed. Based on these above, the improved RSSI algorithm-correction geometric measurement based on weighted is proposed. Finally, utilizing this algorithm to design and implement the localization nodes, which have the CC2431 wireless microcontroller on them. The simulation and experimental results show that the accuracy of this localization algorithm improved about 2%, comparing with the regular algorithms.

scholarly journals Wireless Sensor Network Localization Based On A Mobile Beacon And Tsvm

2014 ◽  
Vol 14 (5) ◽  
pp. 98-107 ◽  
Author(s):  
Jiang Xu ◽  
Huanyan Qian ◽  
Huan Dai ◽  
Jianxin Zhu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Support Vector ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Network Localization ◽  
Gps Devices ◽  
Mobile Beacon

Abstract In this paper a new wireless sensor network localization algorithm, based on a mobile beacon and TSVM (Transductive Support Vector Machines) is proposed, which is referred to as MTSVM. The new algorithm takes advantage of a mobile beacon to generate virtual beacon nodes and then utilizes the beacon vector produced by the communication between the nodes to transform the problem of localization into one of classification. TSVM helps to minimize the error of classification of unknown fixed nodes (unlabeled samples). An auxiliary mobile beacon is designed to save the large volumes of expensive sensor nodes with GPS devices. As shown by the simulation test, the algorithm achieves good localization performance.

Localization Accuracy Improved Methods for Range-Free Localization Schemes in Wireless Sensor Network

2010 ◽  
Vol 437 ◽  
pp. 462-466
Author(s):  
Jia Wen Hu ◽  
Xiao Fen Yu ◽  
Biao Wang ◽  
Zhi Qiang Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Cost ◽  
Signal Strength ◽  
Wireless Sensor ◽  
Location Information ◽  
Received Signal Strength Indicator ◽  
Localization Accuracy ◽  
Improved Methods ◽  
Range Free

Location information is the most important for wireless sensor network (WSN). Due to the limitation of energy, cost and influence of environment, range-free localization schemes are more suitable for WSN despite of their low localization accuracy. Two methods, which are improved grids SCAN and multiple locating and averaging scheme, are presented to improve localization accuracy of range-free localization schemes and performed through performance evaluation based on ROCRSSI (Ring Overlapping based on Comparison of Received Signal Strength Indicator). By simulation it is concluded that ROCRSSI applying both methods can get better localization performances.

scholarly journals Research on Wireless Sensor Network Security Location Based on Received Signal Strength Indicator Sybil Attack

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hongbin Wang ◽  
Liping Feng
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Transmission Function ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Time Inconsistency ◽  
Wireless Sensor ◽  
Sybil Attack ◽  
Received Signal Strength Indicator ◽  
Sensor Network Security

This paper studies the security location mechanism of the sensor network node under the attack of Sybil and analyzes the safe attacks which are possibly accepted and safe requirement in the location system. Since RSSI (Received Signal Strength Indicator) possesses the energy transmission function, different transmission energy will cause it to produce different RSSI readings. Furthermore, this kind of method cannot increase the burden on Wireless Sensor Network (WSN). It conducts an analysis between two receiving nodes, compares RSSI ratios to tickle the problem of time inconsistency of RSSI, and sets a threshold to detect Sybil by the emulation results. Research shows that the ratio value of different receiving nodes by using RSSI can resolve time difference because of the RSSI or unreliability which results from the asymmetry of transmission ratio. The thesis makes a comparison that the number of receiving nodes has an influence on attack effect. Utilizing the RSSI ratio values can exactly detect the Sybil attack. Emulation findings demonstrate that the detection method put forward by the thesis owns better security.

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